Computational systems and methods for regulating information flow during interactions

ABSTRACT

Methods, apparatuses, computer program products, devices and systems are described that carry out accepting at least one indication of an interaction involving at least one member of a network; creating a persona corresponding to the at least one member of a network, wherein the persona is at least partly based on the indication of an interaction; and presenting the persona for use in the interaction involving the at least one member of the network.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is related to and claims the benefit of theearliest available effective filing date(s) from the following listedapplication(s) (the “Related Applications”) (e.g., claims earliestavailable priority dates for other than provisional patent applicationsor claims benefits under 35 USC §119(e) for provisional patentapplications, for any and all parent, grandparent, great-grandparent,etc. applications of the Related Application(s)). All subject matter ofthe Related Applications and of any and all parent, grandparent,great-grandparent, etc. applications of the Related Applications,including any priority claims, is incorporated herein by reference tothe extent such subject matter is not inconsistent herewith.

RELATED APPLICATIONS

For purposes of the USPTO extra-statutory requirements, the presentapplication constitutes a continuation of U.S. patent application Ser.No. 13/373,542, entitled COMPUTATIONAL SYSTEMS AND METHODS FORREGULATING INFORMATION FLOW DURING INTERACTIONS, naming Marc E. Davis,Matthew G. Dyor, William Gates, Xuedong Huang, Roderick A. Hyde, EdwardK. Y. Jung, Jordin T. Kare, Royce A. Levien, Richard T. Lord, Robert W.Lord, Qi Lu, Mark A. Malamud, Nathan P. Myhrvold, Satya Nadella, DanielReed, Harry Shum, Clarence T. Tegreene, and Lowell L. Wood, Jr. asinventors, filed 16 Nov. 2011, which is currently co-pending, or is anapplication of which a currently co-pending application is entitled tothe benefit of the filing date.

For purposes of the USPTO extra-statutory requirements, the presentapplication constitutes a continuation-in-part of U.S. patentapplication Ser. No. 13/199,832, entitled COMPUTATIONAL SYSTEMS ANDMETHODS FOR LINKING USERS OF DEVICES, naming Marc E. Davis, Matthew G.Dyor, William Gates, Xuedong Huang, Roderick A. Hyde, Edward K. Y. Jung,Royce A. Levien, Richard T. Lord, Robert W. Lord, Qi Lu, Mark A.Malamud, Nathan P. Myhrvold, Satya Nadella, Daniel Reed, Harry Shum,Clarence T. Tegreene, and Lowell L. Wood, Jr. as inventors, filed 7 Sep.2011 which is currently co-pending, or is an application of which acurrently co-pending application is entitled to the benefit of thefiling date.

For purposes of the USPTO extra-statutory requirements, the presentapplication constitutes a continuation-in-part of U.S. patentapplication Ser. No. 13/199,829, entitled COMPUTATIONAL SYSTEMS ANDMETHODS FOR LINKING USERS OF DEVICES, naming Marc E. Davis, Matthew G.Dyor, William Gates, Xuedong Huang, Roderick A. Hyde, Edward K. Y. Jung,Royce A. Levien, Richard T. Lord, Robert W. Lord, Qi Lu, Mark A.Malamud, Nathan P. Myhrvold, Satya Nadella, Daniel Reed, Harry Shum,Clarence T. Tegreene, and Lowell L. Wood, Jr. as inventors, filed 9 Sep.2011 which is currently co-pending, or is an application of which acurrently co-pending application is entitled to the benefit of thefiling date.

For purposes of the USPTO extra-statutory requirements, the presentapplication constitutes a continuation-in-part of U.S. patentapplication Ser. No. 13/200,806, entitled COMPUTATIONAL SYSTEMS ANDMETHODS FOR DISAMBIGUATING SEARCH TERMS CORRESPONDING TO NETWORKMEMBERS, naming Marc E. Davis, Matthew G. Dyor, William Gates, XuedongHuang, Roderick A. Hyde, Edward K. Y. Jung, Royce A. Levien, Richard T.Lord, Robert W. Lord, Qi Lu, Mark A. Malamud, Nathan P. Myhrvold, SatyaNadella, Daniel Reed, Harry Shum, Clarence T. Tegreene, and Lowell L.Wood, Jr. as inventors, filed 30 Sep. 2011 which is currentlyco-pending, or is an application of which a currently co-pendingapplication is entitled to the benefit of the filing date.

For purposes of the USPTO extra-statutory requirements, the presentapplication constitutes a continuation-in-part of U.S. patentapplication Ser. No. 13/200,810, entitled COMPUTATIONAL SYSTEMS ANDMETHODS FOR DISAMBIGUATING SEARCH TERMS CORRESPONDING TO NETWORKMEMBERS, naming Marc E. Davis, Matthew G. Dyor, William Gates, XuedongHuang, Roderick A. Hyde, Edward K. Y. Jung, Royce A. Levien, Richard T.Lord, Robert W. Lord, Qi Lu, Mark A. Malamud, Nathan P. Myhrvold, SatyaNadella, Daniel Reed, Harry Shum, Clarence T. Tegreene, and Lowell L.Wood, Jr. as inventors, filed 30 Sep. 2011 which is currentlyco-pending, or is an application of which a currently co-pendingapplication is entitled to the benefit of the filing date.

The United States Patent Office (USPTO) has published a notice to theeffect that the USPTO's computer programs require that patent applicantsreference both a serial number and indicate whether an application is acontinuation, continuation-in-part, or divisional of a parentapplication. Stephen G. Kunin, Benefit of Prior-Filed Application, USPTOOfficial Gazette Mar. 18, 2003. The present Applicant Entity(hereinafter “Applicant”) has provided above a specific reference to theapplication(s) from which priority is being claimed as recited bystatute. Applicant understands that the statute is unambiguous in itsspecific reference language and does not require either a serial numberor any characterization, such as “continuation” or“continuation-in-part,” for claiming priority to U.S. patentapplications. Notwithstanding the foregoing, Applicant understands thatthe USPTO's computer programs have certain data entry requirements, andhence Applicant has provided designation(s) of a relationship betweenthe present application and its parent application(s) as set forthabove, but expressly points out that such designation(s) are not to beconstrued in any way as any type of commentary and/or admission as towhether or not the present application contains any new matter inaddition to the matter of its parent application(s).

All subject matter of the Related Applications and of any and allparent, grandparent, great-grandparent, etc. applications of the RelatedApplications is incorporated herein by reference to the extent suchsubject matter is not inconsistent herewith.

TECHNICAL FIELD

This description relates to data capture and data handling techniques.

SUMMARY

An embodiment provides a system. In one implementation, the systemincludes but is not limited to circuitry for accepting at least oneindication of an interaction involving at least one member of a network;circuitry for creating a persona corresponding to the at least onemember of a network, wherein the persona is at least partly based on theindication of an interaction; and circuitry for presenting the personafor use in the interaction involving the at least one member of thenetwork. In addition to the foregoing, other system aspects aredescribed in the claims, drawings, and text forming a part of thepresent disclosure.

In one or more various aspects, related systems include but are notlimited to circuitry and/or programming for effecting theherein-referenced method aspects; the circuitry and/or programming canbe virtually any combination of hardware, software, and/or firmwareconfigured to effect the herein-referenced method aspects depending uponthe design choices of the system designer.

In one or more various aspects, related systems include but are notlimited to computing means and/or programming for effecting theherein-referenced method aspects; the computing means and/or programmingmay be virtually any combination of hardware, software, and/or firmwareconfigured to effect the herein-referenced method aspects depending uponthe design choices of the system designer.

An embodiment provides a computer-implemented method. In oneimplementation, the method includes but is not limited to accepting atleast one indication of an interaction involving at least one member ofa network; creating a persona corresponding to the at least one memberof a network, wherein the persona is at least partly based on theindication of an interaction; and presenting the persona for use in theinteraction involving the at least one member of the network. Inaddition to the foregoing, other method aspects are described in theclaims, drawings, and text forming a part of the present disclosure.

An embodiment provides an article of manufacture including a computerprogram product. In one implementation, the article of manufactureincludes but is not limited to a signal-bearing medium configured by oneor more instructions related to (a) accepting at least one indication ofan interaction involving at least one member of a network; (b) creatinga persona corresponding to the at least one member of a network, whereinthe persona is at least partly based on the indication of aninteraction; and (c) presenting the persona for use in the interactioninvolving the at least one member of the network. In addition to theforegoing, other computer program product aspects are described in theclaims, drawings, and text forming a part of the present disclosure.

An embodiment provides a system. In one implementation, the systemincludes but is not limited to a computing device and instructions. Theinstructions when executed on the computing device cause the computingdevice to (a) accept at least one indication of an interaction involvingat least one member of a network; (b) create a persona corresponding tothe at least one member of a network, wherein the persona is at leastpartly based on the indication of an interaction; and (c) present thepersona for use in the interaction involving the at least one member ofthe network. In addition to the foregoing, other system aspects aredescribed in the claims, drawings, and text forming a part of thepresent disclosure.

In addition to the foregoing, various other method and/or system and/orprogram product aspects are set forth and described in the teachingssuch as text (e.g., claims and/or detailed description) and/or drawingsof the present disclosure.

The foregoing is a summary and thus may contain simplifications,generalizations, inclusions, and/or omissions of detail; consequently,those skilled in the art will appreciate that the summary isillustrative only and is NOT intended to be in any way limiting. Otheraspects, features, and advantages of the devices and/or processes and/orother subject matter described herein will become apparent in theteachings set forth herein.

BRIEF DESCRIPTION OF THE FIGURES

With reference now to FIG. 1, shown is an example of a system forlinking users of devices in which embodiments may be implemented,perhaps in a device and/or through a network, which may serve as acontext for introducing one or more processes and/or devices describedherein.

FIG. 2 illustrates certain alternative embodiments of the system forlinking users of devices of FIG. 1.

With reference now to FIG. 3, shown is an example of an operational flowrepresenting example operations related to linking users of devices,which may serve as a context for introducing one or more processesand/or devices described herein.

FIG. 4 illustrates an alternative embodiment of the example operationalflow of FIG. 3.

FIG. 5 illustrates an alternative embodiment of the example operationalflow of FIG. 3.

FIG. 6 illustrates an alternative embodiment of the example operationalflow of FIG. 3.

FIG. 7 illustrates an alternative embodiment of the example operationalflow of FIG. 3.

FIG. 8 illustrates an alternative embodiment of the example operationalflow of FIG. 3.

FIG. 9 illustrates an alternative embodiment of the example operationalflow of FIG. 3.

FIG. 10 illustrates an alternative embodiment of the example operationalflow of FIG. 3.

FIG. 11 illustrates an alternative embodiment of the example operationalflow of FIG. 3.

FIG. 12 illustrates an alternative embodiment of the example operationalflow of FIG. 3.

FIG. 13 illustrates an alternative embodiment of the example operationalflow of FIG. 3.

With reference now to FIG. 14, shown is a partial view of an examplearticle of manufacture including a computer program product thatincludes a computer program for executing a computer process on acomputing device related to linking users of devices, which may serve asa context for introducing one or more processes and/or devices describedherein.

With reference now to FIG. 15, shown is an example device in whichembodiments may be implemented related to linking users of devices,which may serve as a context for introducing one or more processesand/or devices described herein.

FIG. 16 illustrates an alternative embodiment of the example operationalflow of FIG. 3.

With reference now to FIG. 17, shown is an example of a system forregulating information flow during interactions in which embodiments maybe implemented, perhaps in a device and/or through a network, which mayserve as a context for introducing one or more processes and/or devicesdescribed herein.

With reference now to FIG. 18, shown is an example of an operationalflow representing example operations related to regulating informationflow during interactions, which may serve as a context for introducingone or more processes and/or devices described herein.

FIG. 19 illustrates an alternative embodiment of the example operationalflow of FIG. 18.

FIG. 20 illustrates an alternative embodiment of the example operationalflow of FIG. 18.

FIG. 21 illustrates an alternative embodiment of the example operationalflow of FIG. 18.

FIG. 22 illustrates an alternative embodiment of the example operationalflow of FIG. 18.

FIG. 23 illustrates an alternative embodiment of the example operationalflow of FIG. 18.

FIG. 24 illustrates an alternative embodiment of the example operationalflow of FIG. 18.

With reference now to FIG. 25, shown is a partial view of an examplearticle of manufacture including a computer program product thatincludes a computer program for executing a computer process on acomputing device related to regulating information flow duringinteractions, which may serve as a context for introducing one or moreprocesses and/or devices described herein.

With reference now to FIG. 26, shown is an example device in whichembodiments may be implemented related to regulating information flowduring interactions, which may serve as a context for introducing one ormore processes and/or devices described herein.

DETAILED DESCRIPTION

In the following detailed description, reference is made to theaccompanying drawings, which form a part hereof. In the drawings,similar symbols typically identify similar components, unless contextdictates otherwise. The illustrative embodiments described in thedetailed description, drawings, and claims are not meant to be limiting.Other embodiments may be utilized, and other changes may be made,without departing from the spirit or scope of the subject matterpresented here.

FIG. 1 illustrates an example system 100 in which embodiments may beimplemented. The system 100 includes a unique identifier unit 102. Theunique identifier unit 102 may contain, for example, device-identifieracceptor module 104 and network-participation identifier acceptor module106. Unique identifier unit 102 may communicate over a network ordirectly with device-identifier custodian 110 to acceptdevice-identifier data 108. Unique identifier unit 102 may alsocommunicate over a network or directly with network-participationidentifier custodian 114 to accept network-participation identifier data112 associated with a verified real-world user 120 associated with theat least one communication device. Optionally, unique identifier unit102 may also accept geodata 116 or financial account data 118. Uniqueidentifier unit 102 may also include identity prediction module 122 forassociating network-participation identifier data with a verifiedreal-world user 120 associated with a communication device.

In FIG. 1, unique identifier unit 102 may assign a unique identifierbased on accepted device-identifier data 108 and acceptednetwork-participation identifier data 112. Optionally, unique identifierunit 102 may assign geodata 116 and/or financial account data 118 to anassigned unique identifier.

In FIG. 1, the unique identifier unit 102 is illustrated as possiblybeing included within a system 100. Of course, virtually any kind ofcomputing device may be used to implement the special purpose uniqueidentifier unit 102, such as, for example, a workstation, a desktopcomputer, a networked computer, a server, a collection of servers and/ordatabases, a virtual machine running inside a computing device, a mobilecomputing device, or a tablet PC.

Additionally, not all of the unique identifier unit 102 need beimplemented on a single computing device. For example, the uniqueidentifier unit 102 may be implemented and/or operable on a remotecomputer, while a user interface and/or local instance of the uniqueidentifier unit 102 are implemented and/or occur on a local computer.Further, aspects of the unique identifier unit 102 may be implemented indifferent combinations and implementations than that shown in FIG. 1.For example, functionality of a user interface may be incorporated intothe unique identifier unit 102. The unique identifier unit 120 mayperform simple data relay functions and/or complex data analysis,including, for example, fuzzy logic and/or traditional logic steps.Further, many methods of assigning unique identifiers described hereinor known in the art may be used, including, for example, algorithms usedin generating globally unique identifiers, universally uniqueidentifiers, and/or other random number generation methods. In someembodiments, the unique identifier unit 102 may assign uniqueidentifiers based on device-identifier data 108 and/ornetwork-participation identifier data 112 available as updates through anetwork.

Unique identifier unit 102 may access data stored in virtually any typeof memory that is able to store and/or provide access to information in,for example, a one-to-many, many-to-one, and/or many-to-manyrelationship. Such a memory may include, for example, a relationaldatabase and/or an object-oriented database, examples of which areprovided in more detail herein.

FIG. 2 illustrates certain alternative embodiments of the system 100 ofFIG. 1. In FIG. 2, The unique identifier unit 102 may also includeunique identifier compiler logic 238 and or encryption protocol logic240. Unique identifier unit 102 may communicate over a network ordirectly with device-identifier custodian 110 to acceptdevice-identifier data 108, perhaps in the form of device identifier 230from communication device 228. Unique identifier unit 102 may alsocommunicate over a network or directly with network-participationidentifier custodian 114 to accept network-participation identifier data112 associated with a verified real-world user 120 associated with theat least one communication device, perhaps from social network 232,business network 234, and/or other network 236.

In this way, the unique identifier unit 102 may generate a compiledand/or encrypted list of unique identifiers that are optionally codedwith or otherwise linked to geodata and/or financial account data.

In some embodiments, unique identifier compiler logic 112 may create acompiled set of composite identifiers that can be used to disambiguatesearch results in the network based on device-identifier data, networkparticipation identifier data, and/or geodata, for example. Uniqueidentifier unit 102 can be operated by a telecom company or by a socialor other network owner, or by both in cooperation with each other. Acompiled list of unique identifiers as discussed herein can representall or substantially all unique user devices in a given social networkor other communications network, e.g., wireless network, email network,or the like.

A directory of uniquely-identified devices can serve as the foundationfor searching within a social network, and for facilitating financialtransactions via the device for members of the social network associatedwith the device.

In some embodiments, unique identifier unit 102 may also includeidentity prediction module 122 for associating network-participationidentifier data with a verified real-world user 120 associated with acommunication device 228. Identity prediction module 122 may includevarious search and/or matching functions for associatingnetwork-participation identifier data 112 with a verified real-worlduser 120 associated with a communications device 228. For example,identity prediction module 122 may include de-anonymization module 244,which in turn may include real-name profiling module 246. Identityprediction module 122 may also include web history tracking module 248,media content tracking module 250, and/or app list tracking module 252.

For the purposes of this application, SIM as used herein includesmini-SIM, micro-SIM, Universal Subscriber Identity Module, CDMASubscriber Identity Module, Universal Integrated Circuit Card, RemovableUser Identity Module, virtual SIM, and other variants of the subscriberidentity module described herein and understood by those of ordinaryskill in the art.

As referenced herein, the unique identifier unit 102 may be used toperform various data querying and/or recall techniques with respect tothe device-identifier data 108 and/or network-participation identifierdata 112, in order to assign a unique identifier. For example, where thenetwork-participation identifier data 112 is organized, keyed to, and/orotherwise accessible using one or more user accounts such as socialnetwork, email, or the like, unique identifier unit 102 may employvarious Boolean, statistical, and/or semi-boolean searching techniquesto assign a unique identifier. Similarly, for example, wheredevice-identifier data 108 is organized, keyed to, and/or otherwiseaccessible using one or more device-identifier custodian 110, variousBoolean, statistical, and/or semi-boolean searching techniques may beperformed by unique identifier unit 102 to assign a unique identifier.

Many examples of databases and database structures may be used inconnection with the unique identifier unit 102. Such examples includehierarchical models (in which data is organized in a tree and/orparent-child node structure), network models (based on set theory, andin which multi-parent structures per child node are supported), orobject/relational models (combining the relational model with theobject-oriented model).

Still other examples include various types of eXtensible Mark-upLanguage (XML) databases. For example, a database may be included thatholds data in some format other than XML, but that is associated with anXML interface for accessing the database using XML. As another example,a database may store XML data directly. Additionally, or alternatively,virtually any semi-structured database may be used, so that context maybe provided to/associated with stored data elements (either encoded withthe data elements, or encoded externally to the data elements), so thatdata storage and/or access may be facilitated.

Such databases, and/or other memory storage techniques, may be writtenand/or implemented using various programming or coding languages. Forexample, object-oriented database management systems may be written inprogramming languages such as, for example, C++ or Java. Relationaland/or object/relational models may make use of database languages, suchas, for example, the structured query language (SQL), which may be used,for example, for interactive queries for disambiguating informationand/or for gathering and/or compiling data from the relationaldatabase(s).

For example, SQL or SQL-like operations over one or moredevice-identifier data 108 and/or network-participation identifier data112 may be performed, or Boolean operations using a device-identifierdata 108 and/or network-participation identifier data 112 may beperformed. For example, weighted Boolean operations may be performed inwhich different weights or priorities are assigned to one or more of thedevice-identifier data 108 and/or network-participation identifier data112, including various network participation aliases associated with aparticular verified real-world user, perhaps relative to one another.For example, a number-weighted, exclusive-OR operation may be performedto request specific weightings of network participation identifiers.

Following are a series of flowcharts depicting implementations. For easeof understanding, the flowcharts are organized such that the initialflowcharts present implementations via an example implementation andthereafter the following flowcharts present alternate implementationsand/or expansions of the initial flowchart(s) as either sub-componentoperations or additional component operations building on one or moreearlier-presented flowcharts. Those having skill in the art willappreciate that the style of presentation utilized herein (e.g.,beginning with a presentation of a flowchart presenting an exampleimplementation and thereafter providing additions to and/or furtherdetails in subsequent flowcharts) generally allows for a rapid and easyunderstanding of the various process implementations. In addition, thoseskilled in the art will further appreciate that the style ofpresentation used herein also lends itself well to modular and/orobject-oriented program design paradigms.

FIG. 3 illustrates an operational flow 300 representing exampleoperations related to linking users of devices. In FIG. 3 and infollowing figures that include various examples of operational flows,discussion and explanation may be provided with respect to theabove-described system environments of FIGS. 1-2, and/or with respect toother examples and contexts. However, it should be understood that theoperational flows may be executed in a number of other environments andcontexts including that of FIG. 15, and/or in modified versions of FIGS.1-2. Also, although the various operational flows are presented in thesequence(s) illustrated, it should be understood that the variousoperations may be performed in other orders than those which areillustrated, or may be performed concurrently.

After a start operation, operation 310 depicts acceptingdevice-identifier data corresponding to at least one communicationdevice. For example, unique identifier unit 102 and/or device-identifieracceptor module 104 can accept device-identifier data 108 from atelecommunications carrier 220, for example in the form of a UniqueDevice Identifier (UDID) for an iPhone or iPod Touch. The UDID is asequence of 40 letters and numbers that is specific to each iPhone oriPod Touch. It may look something like this:2b6f0cc904d137be2e1730235f5664094b831186. Other examples of sources ofdevice-identifier data 108 include voice-over-internet-protocol serviceproviders such as Skype (peer-to-peer VoIP), and wireless carriers suchas Verizon Wireless (CDMA-based wireless communication). Other examplesof device-identifier data 108 include Media Access Control addresses(MAC address) and International Mobile Equipment Identity numbers(IMEI).

Operation 320 depicts accepting network-participation identifier dataassociated with a verified real-world user associated with the at leastone communication device. For example, unique identifier unit 102 and/ornetwork-participation identifier acceptor module 106 may accept fromFacebook a username associated with a verified real-world user having aniPhone and corresponding account with a telecommunications company. Inanother example, unique identifier unit 102 may accept from LinkedIn thename of a person associated with a videoconferencing device andcorresponding account with a videoconferencing service such as WebEx Webconferencing. In another example, unique identifier unit 102 may acceptfrom Google the email address of a person associated with an Androidphone and corresponding account with a wireless carrier.

In some embodiments, network-participation identifier custodian 114 anddevice-identifier custodian will cooperate to provide the necessarynetwork-participation identifier data 112 and device-identifier data 108to unique identifier unit 108. For example, Facebook may provideusernames, images, birthdates, telephone numbers, or other data that ithas about the verified real-world users of its social network to aconsortium of telecommunications carriers 220 (this may optionallyinvolve an opting-in step whereby users of Facebook affirmativelyapprove this action), who may provide device-identifier data 108.Assigning a unique identifier (discussed below) for eachnetwork-user-associated device across each of the carriers in theconsortium may result in a directory that is particularly valuable forthe telecommunications carriers, who can then provide directorysearching, support, and disambiguation for a potentially large fractionof the Facebook social network. Such a directory will likely be of equalinterest and value to networks including Facebook in this example, forthe same reasons. For example, a cross-carrier directory of Facebookmembers with associated phone numbers would be an added feature forFacebook that could significantly enhance the social informationprovided by the network.

Operation 330 depicts assigning a unique identifier at least partlybased on the device-identifier data and the network-participationidentifier data. For example, unique identifier unit 102, upon acceptingdevice-identifier data 108 and network-participation identifier data 112associated with a verified real-world user 120 associated with the atleast one communication device, may assign a randomly-generated 32-bitunique identifier. In the iPhone example above, unique identifier unit102 may accept the iPhone's unique device identifier (UDID) as thedevice-identifier data 108, accept an iTunes username associated with auser with a valid credit card and security code as thenetwork-participation identifier data 112 associated with a verifiedreal-world user 120 associated with the at least one communicationdevice, and assign a unique identifier to the device and username pair.

As another example, unique identifier unit 102 may accept the MACaddress of a networked computer, as the device-identifier data 108,accept an Outlook email address associated with a user with a verifiedbiometric measurement as the network-participation identifier data 112associated with a verified real-world user 120 associated with the atleast one communication device, and assign a unique identifier to thecomputer and email address pair.

As another example, unique identifier unit 102 may accept a mobilephone's integrated circuit card ID (ICC-ID) as the device-identifierdata 108, accept a Facebook username associated with a user with a validFacebook Credits account as the network-participation identifier data112 associated with a verified real-world user 120 associated with theat least one communication device, and assign a unique identifier to themobile phone and Facebook username pair.

In some embodiments, unique identifier unit 102 may include an identityprediction algorithm such as a de-anonymization algorithm, a real-nameprofiling algorithm, a web history tracking algorithm, media contenttracking algorithm, and/or an app list tracking algorithm. Thesealgorithms may aid in the association of network-participationidentifier data with a verified real-world user 120 associated with thecommunication device 228, where those associations are not provideddirectly by a device-identifier custodian 110 and/or anetwork-participation identifier custodian 114.

FIG. 4 illustrates alternative embodiments of the example operationalflow 300 of FIG. 3. FIG. 4 illustrates example embodiments where theaccepting operation 310 may include at least one additional operation.Additional operations may include operation 400, 402, 404, and/oroperation 406.

Operation 400 depicts accepting device-identifier data corresponding toat least one of a mobile phone, a wired telephone, avoice-over-internet-protocol telephone, a tablet computer, a notebookcomputer, a laptop computer, a desktop computer, or a networkedtelevision. For example, unique identifier unit 102 and/ordevice-identifier acceptor module 104 may accept device-identifier datacorresponding to at least one of a mobile phone, a wired telephone, avoice-over-internet-protocol telephone, a tablet computer, a notebookcomputer, a laptop computer, a desktop computer, or a networkedtelevision. For example, device-identifier acceptor module 104 mayaccept a mobile phone's mobile equipment identifier, a land line'stelephone number, or a networked computer's media access control address(MAC address) or internet protocol address (IP address).

Device-identifier data 108 may be accepted in different forms dependingon the device identified. For example, an IP address or MAC address maybe used to identify a computer.

Every device connected to the public internet is assigned a uniquenumber known as an internet protocol address (IP address). IP addressesconsist of four numbers separated by periods (also called a“dotted-quad”) and look something like 127.0.0.1. Since these numbersare usually assigned to internet service providers within region-basedblocks, an IP address can often be used to identify the region orcountry from which a computer is connecting to the Internet. An IPaddress can sometimes be used to show the user's general location. An IPaddress may also be assigned to a Host name, which may be easier toremember. Hostnames may be looked up to find IP addresses, andvice-versa. At one time internet service providers issued one IP addressto each user. These are static IP addresses. With the increased numberof issued IP addresses, internet service providers now issue IPaddresses in a dynamic fashion out of a pool of IP addresses usingdynamic host configuration protocol (DHCP), which provides a centraldatabase for keeping track of computers that have been connected to thenetwork. This prevents two computers from accidentally being configuredwith the same IP address. These are referred to as dynamic IP addresses.In addition to users connecting to the internet, with virtual hosting, asingle machine can act like multiple machines, with multiple domainnames and IP addresses.

MAC addresses are unique identifiers assigned to network interfaces forcommunications on the physical network segment. They are most oftenassigned by the manufacturer of a network interface card (NIC) and arestored in its hardware, the card's read-only memory, or some otherfirmware mechanism. If assigned by the manufacturer, a MAC addressusually encodes the manufacturer's registered identification number andmay be referred to as the burned-in address. It may also be known as anEthernet hardware address (EHA), hardware address, or physical address.A network node may have multiple NICs and will then have one unique MACaddress per NIC.

A subscriber identity module or subscriber identification module (SIM)is an integrated circuit that securely stores the service-subscriber keyor international mobile subscriber identity (IMSI) used to identify asubscriber on mobile telephony devices (such as mobile phones andcomputers). A SIM card typically contains its unique serial number(integrated circuit card identifier or ICCID), an internationally uniquenumber of the mobile user (IMSI), security authentication and cipheringinformation, temporary information related to the local network, a listof the services the user has access to and two passwords: a personalidentification number (PIN) for usual use and a PIN unlock code (PUC)for unlocking. A SIM card may also store other carrier-specific datasuch as the SMSC (Short Message Service Center) number, Service ProviderName (SPN), Service Dialing Numbers (SDN), Advice-Of-Charge parametersand Value Added Service (VAS) applications.

A SIM card's ICCID is stored in the SIM card and also engraved orprinted on the SIM card body. The ICCID is typically composed of anissuer identification number (IIN), an individual account identificationnumber, and a check digit.

SIM cards are identified on their individual operator networks by aunique international mobile subscriber identity number or IMSI. Mobileoperators connect mobile phone calls and communicate with their marketSIM cards using their IMSIs. The format is: the first 3 digits representthe Mobile Country Code (MCC), the next 2 or 3 digits represent theMobile Network Code (MNC), and the next digits represent the mobilestation identification number.

SIM cards may also orthogonally store a number of SMS messages and phonebook contacts. A SIM is held on a removable SIM card, which can betransferred between different mobile devices.

Operation 402 depicts accepting telephony device-identifier dataincluding a telephone number associated with the telephony device. Forexample, unique identifier unit 102 may accept a ten-digit telephonenumber or a seven-digit telephone number from a telecommunicationscarrier 220 as the device-identifier data 108. The number contains theinformation necessary to identify uniquely the intended endpoint for thetelephone call. Each such endpoint must have a unique number within thepublic switched telephone network.

Operation 404 depicts accepting at least one of subscriber identitymodule data or integrated circuit card identifier data corresponding toat least one communication device. For example, unique identifier unit102 may accept an international mobile subscriber identity (IMSI) from amobile phone's SIM card from a telecommunications carrier 220 as thedevice-identifier data 108. As another example, device-identifieracceptor module 104 may accept from a wireless communications service222 an integrated circuit card identifier number from a SIM card for amobile phone.

Operation 406 depicts accepting mobile equipment identifier datacorresponding to at least one communication device. For example, uniqueidentifier unit 102 may accept a mobile equipment identifiercorresponding to a mobile handset from a telecommunications carrier 220or wireless communications service 222. A Mobile Equipment IDentifier(MEID) is a globally unique 56-bit identification number for a physicalpiece of mobile equipment. Equipment identifiers are “burned” into adevice and are used as a means to facilitate mobile equipmentidentification and tracking. Additionally, MEIDs are coordinated withInternational Mobile Equipment Identifiers (IMEIs), facilitating globalroaming and harmonization between 3G technologies as a universal mobileequipment identifier. The MEID is a 14-digit hexadecimal value. The MEIDis capable of being transmitted over the air upon a request from thenetwork. The MEID is composed mainly of two basic components, themanufacturer code and the serial number.

FIG. 5 illustrates alternative embodiments of the example operationalflow 300 of FIG. 3. FIG. 5 illustrates example embodiments where theaccepting operation 310 may include at least one additional operation.Additional operations may include operation 500, 502, and/or operation504.

Operation 500 depicts accepting international mobile subscriber identitydata corresponding to at least one communication device. For example,device-identifier acceptor module 104 may accept an international mobilesubscriber identity (IMSI) from a mobile phone's SIM card from awireless communications service 222 as the device-identifier data 108.An International Mobile Subscriber Identity or IMSI is a uniqueidentification associated with all GSM and UMTS network mobile phoneusers. It is stored as a 64-bit field in the SIM inside the phone and issent by the phone to the network. It is also used for acquiring otherdetails of the mobile device in the Home Location Register (HLR) or aslocally copied in the Visitor Location Register. To preventeavesdroppers identifying and tracking the subscriber on the radiointerface, the IMSI is sent as rarely as possible and arandomly-generated temporary mobile subscriber identity (TMSI) is sentinstead. The IMSI is used in any mobile network that interconnects withother networks. This number is kept in the phone directly or in theremovable user identity module (R-UIM) card, a card developed for CDMAhandsets that extends the GSM SIM card to CDMA phones and networks.

Operation 502 depicts accepting electronic serial number datacorresponding to at least one communication device. For example, uniqueidentifier unit 102 may accept an electronic serial number from a mobilephone's SIM card from a telecommunications carrier 220 as thedevice-identifier data 108. As another example, device-identifieracceptor module 104 may accept from a wireless communications service222 an electronic serial number from a SIM card for a CDMA-based mobilephone.

Operation 504 depicts accepting device-identifier data corresponding toat least one communication device that is linked to at least one billingaccount. For example, unique identifier unit 102 may accept a mobileequipment identifier from a mobile phone's SIM card from atelecommunications carrier 220, the MEID corresponding to a billingaccount for a subscriber of a wireless service provided by thetelecommunications carrier 220. As another example, device-identifieracceptor module 104 may accept from a wireless communications service222 an IMSI from a SIM card for a mobile phone, the IMSI correspondingto a billing account for a subscriber of the wireless communicationsservice 222.

FIG. 6 illustrates alternative embodiments of the example operationalflow 300 of FIGS. 3 and 5. FIG. 6 illustrates example embodiments wherethe accepting operation 504 may include at least one additionaloperation. Additional operations may include operation 600, 602, and/oroperation 604.

Operation 600 depicts accepting device-identifier data corresponding toat least one communication device that is linked to at least one billingaccount, wherein the at least one billing account comprises a cabletelecommunications billing account. For example, unique identifier unit102 may accept a computer user's MAC address or IP address as the deviceidentifier data 108. In this example, the MAC address or IP address ofthe computer may be linked to a Skype account for billing purposes.

Operation 602 depicts accepting device-identifier data corresponding toat least one communication device that is linked to at least one billingaccount, wherein the at least one billing account comprises a wirelesstelecommunications billing account. For example, unique identifier unit102 may accept from a wireless service provider an IMEI for a mobilephone linked to a billing account for an individual subscriber.

Operation 604 depicts accepting device-identifier data corresponding toat least one communication device that is linked to at least one billingaccount, wherein the at least one wireless telecommunications billingaccount comprises a satellite telecommunications billing account. Forexample, unique identifier unit 102 may accept from a satellite-basedwireless service provider such as LightSquared, a device-identifier fora mobile phone linked to a billing account for an individual subscriber.

FIG. 7 illustrates alternative embodiments of the example operationalflow 300 of FIGS. 3 and 5. FIG. 7 illustrates example embodiments wherethe accepting operation 504 may include at least one additionaloperation. Additional operations may include operation 700, 702, 704,and/or operation 706.

Operation 700 depicts accepting device-identifier data corresponding toat least one communication device that is linked to at least one billingaccount, wherein the at least one billing account comprises a physicaladdress. For example, device-identifier acceptor module 104 may acceptfrom a wireless communications service 222 an IMSI from a SIM card for amobile phone, the IMSI corresponding to a billing account for asubscriber of the wireless communications service 222 at a specificstreet, city, and country address.

Operation 702 depicts accepting device-identifier data corresponding toat least one communication device that is linked to at least one billingaccount, wherein the at least one billing account comprises a bankaccount. For example, device-identifier acceptor module 104 may acceptfrom a wireless communications service 222 an iPhone or iPod Touchdevice identifier, the identifier corresponding to a bank account numberfor a subscriber of the wireless service to the iPhone or iPod Touchdevice.

Operation 704 depicts accepting device-identifier data corresponding toat least one communication device that is linked to at least one billingaccount, wherein the at least one billing account comprises anelectronic payment account. To continue the previous example involvingthe iPhone or iPod Touch device, the wireless service subscription maybe linked to a bank's electronic payment, service, wire transferservice, or the like.

Operation 706 depicts accepting device-identifier data corresponding toat least one communication device that is linked to at least oneelectronic payment account, wherein the electronic payment accountcomprises at least one of a Google Checkout account, an Amazon Paymentsaccount, a PayPal account, or a mobile PayPal account. For example, aunique identifier unit 102 may accept a mobile device ID for an Androidmobile phone from an Android app such as “Android Device ID” availablefor download from the Android Market. The Android mobile device ID,perhaps derived from a wireless network socket, for the mobile phone maycorrespond to a Google Checkout account for the subscriber of thewireless service to the mobile phone.

FIG. 8 illustrates alternative embodiments of the example operationalflow 300 of FIGS. 3 and 5. FIG. 8 illustrates example embodiments wherethe accepting operation 504 may include at least one additionaloperation. Additional operations may include operation 800, 802, and/oroperation 804.

Operation 800 depicts accepting device-identifier data corresponding toat least one communication device that is linked to at least one billingaccount, wherein the at least one billing account comprises a creditcard account. For example, a wireless device's service subscription maybe linked to a user's credit card account.

Operation 802 depicts accepting device-identifier data corresponding toat least one communication device that is linked to at least one billingaccount, wherein the at least one billing account comprises a virtualaccount. For example, to continue the Google Checkout example above, aunique identifier unit 102 may accept a mobile device ID for an Androidmobile phone from an Android app such as “Android Device ID” availablefor download from the Android Market. The Android mobile device ID forthe mobile phone may correspond to a virtual account such as a Facebookcredit account.

Operation 804 depicts accepting device-identifier data corresponding toat least one communication device that is linked to at least one virtualaccount, wherein the virtual account comprises at least one of a virtualwallet or a virtual prepaid credit card. For example, to continue theGoogle Checkout example above, a unique identifier unit 102 may accept amobile device ID for an Android mobile phone from an Android app such as“Android Device ID” available for download from the Android Market. TheAndroid mobile device ID for the mobile phone may correspond to avirtual wallet account such as Google wallet.

FIG. 9 illustrates alternative embodiments of the example operationalflow 300 of FIG. 3. FIG. 9 illustrates example embodiments where theaccepting operation 320 may include at least one additional operation.Additional operations may include operation 900, 902, 904, and/oroperation 906.

Operation 900 depicts accepting network-participation identifier dataassociated with at least one of a user's social security number, auser's national identification card, a user's biometric measurement, auser's passport number, a user's tax identification number, a user'sinternet domain, or a user's authentication certificate. For example,unique identifier unit 102 and/or network-participation identifieracceptor module 106 may accept network-participation identifier dataassociated with at least one of a user's social security number, auser's national identification card, a user's biometric measurement, auser's passport number, a user's tax identification number, a user'sinternet domain, or a user's authentication certificate. For example,network-participation identifier acceptor module 106 may accept aFacebook username as network-participation identifier data, the usernameassociated with a photograph of the user as a biometric measurementverifying that a real-world user is associated with the username. Insome embodiments, an image recognition system may be employed toassociate an image with a specific user. In some embodiments, thereal-world user may be a corporation.

In another example, network-participation identifier acceptor module 106may accept an email address as network-participation identifier data,the email address associated with a social security number on file witha telecommunications company with which the user has a servicesubscription.

As used herein, “network-participation identifier data” may refer to asignifier of belonging in a network, such as an email address; ausername, such as a social networking user name; or other mark such asan image, number, or writing that signifies participation in aparticular network.

Operation 902 depicts accepting social networking data corresponding toat least one verified real-world user of the at least one communicationdevice. For example, unique identifier unit 102 and/ornetwork-participation identifier acceptor module 106 may accept aGoogle+ username as a network-participation identifier datum, whereinthe Google+ username is associated with a photograph of the user havingthe username. In some embodiments, the photograph of the user may beanalyzed by image recognition technologies to identify a person havingspecific geographic, demographic, or other identifying characteristics.

Operation 904 depicts accepting social networking data corresponding toat least one verified real-world user of the at least one communicationdevice, wherein the social networking data comprises at least one of ausername, an @-tagged twitter handle, a corporate login, or a websiteuniform resource locator (URL). For example, unique identifier unit 102and/or network-participation identifier acceptor module 106 may accept ablogger's website URL as a network-participation identifier datum,wherein the website URL is associated with a photograph and/ordescription of the blogger on the website at the website URL.

Operation 906 depicts accepting social networking data corresponding toat least one verified real-world user of the at least one communicationdevice, wherein the social networking data comprises at least one ofFacebook data, Twitter data, or LinkedIn data. For example, uniqueidentifier unit 102 and/or network-participation identifier acceptormodule 106 may accept a LinkedIn username as a network-participationidentifier datum, wherein the username is associated with a publicprofile of a user of the business-related social networking siteLinkedIn.

FIG. 10 illustrates alternative embodiments of the example operationalflow 300 of FIGS. 3 and 9. FIG. 10 illustrates example embodiments wherethe accepting operation 902 may include at least one additionaloperation. Additional operations may include operation 1000, 1002,and/or operation 1004.

Operation 1000 depicts accepting social networking data corresponding toat least one verified real-world user of the at least one communicationdevice, wherein the social networking data comprises at least one ofimage data, constellation of social contact data, or user input data.For example, unique identifier unit 102 and/or network-participationidentifier acceptor module 106 may accept a list of social contacts froma social network such as Facebook or LinkedIn as thenetwork-participation identifier data. In another example, uniqueidentifier unit 102 and/or network-participation identifier acceptormodule 106 may accept a list of email contacts grouped as friends orfamily from an email contact list as the network-participationidentifier data.

Operation 1002 depicts accepting social networking data corresponding toat least one verified real-world user of the at least one communicationdevice, wherein the social networking data comprises data accumulatedfrom multiple sources. For example, unique identifier unit 102 and/ornetwork-participation identifier acceptor module 106 may accept aplurality of usernames sourced from various social networks, eachcorresponding to the same verified real-world user of the at least onecommunication device as the data accumulated from multiple sources. Asanother example, unique identifier unit 102 and/or network-participationidentifier acceptor module 106 may accept a set of photographs of thesame verified real-world user of the at least one communication device,sourced from various social networks as the data accumulated frommultiple sources.

Operation 1004 depicts accepting social networking data corresponding toat least one verified real-world user of the at least one communicationdevice, wherein the social networking data comprises at least one ofdata used to create additional data or data used to find additionaldata. For example, unique identifier unit 102 and/ornetwork-participation identifier acceptor module 106 may accept awebsite URL of a social networking site's videoconferencing or videochatfeed as data (website URL) used to create additional data (streamingvideo of network participants). In another example, unique identifierunit 102 and/or network-participation identifier acceptor module 106 mayaccept a user image or alias that can be used to find other data, forexample as a search term in an reverse-image query or a text query,respectively.

FIG. 11 illustrates alternative embodiments of the example operationalflow 300 of FIG. 3. FIG. 11 illustrates example embodiments where theassigning operation 330 may include at least one additional operation.Additional operations may include operation 1100, 1102, and/or operation1104.

Operation 1100 depicts assigning at least one of a multi-digit decimalnumber, a multi-digit hexadecimal number, or a randomized code as theunique identifier. For example, unique identifier unit 102 may assign atleast one of a multi-digit decimal number, a multi-digit hexadecimalnumber, or a randomized code as the unique identifier. In anotherexample, unique identifier unit 102 may assign a unique identifier usingan algorithm(s) known in the art to generate unique multi-digit decimalnumbers or unique multi-digit hexadecimal numbers. See, e.g., U.S. Pat.No. 8,010,587 (hereby incorporated by reference).

Operation 1102 depicts further comprising encrypting the uniqueidentifier. For example, unique identifier unit 102 and/or encryptionprotocol logic 240 may encrypt the assigned unique identifier.Encrypting the unique identifier may be desirable in cases wheretelecommunications carriers sharing a directory comprised of uniqueidentifiers for the purpose of locating and disambiguating users of oneor more networks, can share the unique identifiers but still protectthem and the underlying data from access by undesirable entities such asspammers and telemarketers. In another example, unique identifier unit102 may encrypt the assigned identifier or associated sensitive personaland/or financial information according to encryption schemes describedherein and known in the art. See, e.g., U.S. Pat. No. 8,010,791 and U.S.Pat. No. 8,010,786 (hereby incorporated by reference).

Operation 1104 depicts further comprising encrypting the uniqueidentifier, wherein the encrypting the unique identifier includesperforming at least one of symmetric key encryption, public keyencryption, hybrid digital signature encryption, using a one-way hashfunction, using a random identifier, or using a pseudo-randomidentifier. For example, unique identifier unit 102 and/or encryptionprotocol logic 240 may encrypt the assigned unique identifier using aone-way hash function, which is easy to compute on every input, but hardto invert given the image of a random input.

FIG. 12 illustrates alternative embodiments of the example operationalflow 300 of FIG. 3. FIG. 12 illustrates example embodiments where theassigning operation 330 may include at least one additional operation.Additional operations may include operation 1200, 1202, 1204, and/oroperation 1206.

Operation 1200 depicts assigning a unique identifier at least partlybased on the device-identifier data and the network-participationidentifier data, further comprising assigning to the unique identifiergeo-locator data from the at least one communication device. Forexample, unique identifier unit 102 may accept geodata 116 from a mobilephone, and then assign that geodata to an assigned unique identifiercorresponding to a device and a network participant. In another example,unique identifier unit 102 may accept geodata 116 in the form of acomputer's IP address, and then assign that geodata to an assignedunique identifier corresponding to the computer and a verified networkparticipant associated with that computer.

Operation 1202 depicts assigning a unique identifier at least partlybased on the device-identifier data and the network-participationidentifier data, further comprising assigning to the unique identifiergeo-locator data from the at least one communication device, wherein thegeo-locator data is assigned via a global positioning satellite functionof the communication device. For example, unique identifier unit 102 mayaccept geodata 116 from a mobile phone having a gps receiver, and thenassign that geodata to an assigned unique identifier corresponding to adevice and a network participant.

Operation 1204 depicts assigning a unique identifier at least partlybased on the device-identifier data and the network-participationidentifier data, further comprising assigning to the unique identifiergeo-locator data from the at least one communication device, wherein thegeo-locator data is derived from at least one of cellular phone towerproximity, Wi-Fi use, user-entered location data, or proximity to atleast one other device. For example, unique identifier unit 102 mayaccept geodata 116 from a smart phone using a Wi-Fi network contained ina database that contains location information for the Wi-Fi network, andthen assign that geodata to an assigned unique identifier correspondingto a device and a network participant.

Operation 1206 depicts assigning a unique identifier at least partlybased on the device-identifier data and the network-participationidentifier data, further comprising assigning to the unique identifiergeo-locator data from the at least one communication device, wherein thegeo-locator data is derived from at least one of a detected vehicle use,a detected user activity, or a detected user location. For example,unique identifier unit 102 may derive geo-locator data from detectedautomobile use, based on, for example, last known location and predictedrange of travel of the automobile. In another example, unique identifierunit 102 may receive or deduce geo-locator data from a detected useractivity, for example, checking in with foursquare at a specificlocation or searching for driving directions in a web browser,respectively.

FIG. 13 illustrates alternative embodiments of the example operationalflow 300 of FIG. 3. FIG. 13 illustrates example embodiments where theassigning operation 330 may include at least one additional operation.Additional operations may include operation 1300, 1302, 1304, and/oroperation 1306.

Operation 1300 depicts assigning a unique identifier at least partlybased on the device-identifier data and the network-participationidentifier data, wherein the unique identifier represents multiplecommunication devices associated with a single user. For example, uniqueidentifier unit 102 may assign a unique identifier at least partly basedon the device-identifier data and the network-participation identifierdata, wherein the unique identifier represents multiple communicationdevices associated with a single user. In another example, uniqueidentifier unit 102 may accept device-identifier data from a mobilephone, a desktop computer, and a laptop computer, each of which isassociated with a single user, for example by virtue of an IMSI or otherSIM data, email data, billing account data, or social networking data.

Operation 1302 depicts assigning a unique identifier at least partlybased on the device-identifier data and the network-participationidentifier data, wherein the unique identifier represents a singlecommunication device associated with multiple users. For example, uniqueidentifier unit 102 may assign a unique identifier at least partly basedon the device-identifier data and the network-participation identifierdata, wherein the unique identifier represents a single communicationdevice associated with multiple users. In another example, uniqueidentifier unit 102 may accept device-identifier data from a mobilephone, the device-identifier data associated with a multiple users, forexample members of a family by virtue of different login data used foraccess to the device and/or different social networking usernames usedon the device.

Operation 1304 depicts assigning a unique identifier at least partlybased on the device-identifier data and the network-participationidentifier data, wherein the unique identifier represents a singlecommunication device associated with a single user. For example, uniqueidentifier unit 102 may assign a unique identifier at least partly basedon the device-identifier data and the network-participation identifierdata, wherein the unique identifier represents a single communicationdevice associated with a single user. As another example, uniqueidentifier unit 102 may assign a unique identifier at least partly basedon a videoconferencing device ID, such as an IP address or a MACaddress, and at least partly based on a username and password for thevideoconference, accompanied by a video image of a user associated withthe username and password, verifying that a real-world user isassociated with the videoconferencing device.

Operation 1306 depicts assigning a unique identifier at least partlybased on the device-identifier data and the network-participationidentifier data, and then adding an assigned unique identifier to aninter-service-provider directory of unique identifiers. For example,unique identifier unit 102 may assign a unique identifier at leastpartly based on the device-identifier data and the network-participationidentifier data, and then adding an assigned unique identifier to aninter-service-provider directory of unique identifiers. In anotherexample, unique identifier unit 102 may assign a unique identifier atleast partly based on SIM data identifying a user's mobile phone, and atleast partly based on subscriber's participation in the wirelessnetwork, as verified, for example, by a social security number for theuser on file with the wireless carrier for the mobile device, forexample, Verizon. Verizon may similarly create unique identifiers forall of the other verified real-world users of its network and theirassociated devices. Other wireless carriers may similarly create uniqueidentifiers for their subscribers and associated devices.

If many wireless carriers agree to share their unique identifier listsand keep them in the same format for use as a global directory of mobilephone users, a comprehensive “white pages” of communications deviceusers becomes possible, across potentially all service providers. Such adirectory could also be keyed to social networking data such as usernameor user image, such that, for example, Facebook users could easily findeach other's device contact information and possibly locationinformation. Inclusion of users' device information in such a directorycould be done on an opt-in basis.

As used herein, a unique identifier based on a device-identifier and anetwork-participant identifier may be keyed to that underlying data.That is, having the unique identifier corresponding to specific devicedata and specific network-participation identifier data associated witha verified real-world user associated with the at least onecommunication device will permit the creator of the unique identifier touse it to call up the specific device data and specific networkparticipation identifier data. This may allow, for example, atelecommunications carrier to disambiguate one user from another havingsimilar or identical network participation identifier data. This can bedone on the basis of different device identifier data for the two userswith similar or identical network participation identifier data, forexample.

FIG. 14 illustrates a partial view of an example article of manufacture1400 that includes a computer program 1404 for executing a computerprocess on a computing device. An embodiment of the example article ofmanufacture 1400 is provided including a signal bearing medium 1402, andmay include one or more instructions for accepting device-identifierdata corresponding to at least one communication device; one or moreinstructions for accepting network-participation identifier dataassociated with a verified real-world user associated with the at leastone communication device; and one or more instructions for assigning aunique identifier at least partly based on the device-identifier dataand the network-participation identifier data. The one or moreinstructions may be, for example, computer executable and/orlogic-implemented instructions. In one implementation, thesignal-bearing medium 1402 may include a computer-readable medium 1406.In one implementation, the signal bearing medium 1402 may include arecordable medium 1408. In one implementation, the signal bearing medium1402 may include a communications medium 1410.

FIG. 15 illustrates an example system 1500 in which embodiments may beimplemented. The system 1500 includes a computing system environment.The system 1500 also illustrates a user 1512 using a device 1504, whichis optionally shown as being in communication with a computing device1502 by way of an optional coupling 1506. The optional coupling 1506 mayrepresent a local, wide-area, or peer-to-peer network, or may representa bus that is internal to a computing device (e.g., in exampleembodiments in which the computing device 1502 is contained in whole orin part within the device 1504). A storage medium 1508 may be anycomputer storage media. In one embodiment, the computing device 1502 mayinclude a virtual machine operating within another computing device. Inan alternative embodiment, the computing device 1502 may include avirtual machine operating within a program running on a remote server.

The computing device 1502 includes computer-executable instructions 1510that when executed on the computing device 1502 cause the computingdevice 1502 to (a) accept device-identifier data corresponding to atleast one communication device; (b) accept network-participationidentifier data associated with a verified real-world user associatedwith the at least one communication device; and (c) assign a uniqueidentifier at least partly based on the device-identifier data and thenetwork-participation identifier data. As referenced above and as shownin FIG. 15, in some examples, the computing device 1502 may optionallybe contained in whole or in part within the device 1504.

In FIG. 15, then, the system 1500 includes at least one computing device(e.g., 1502 and/or 1504). The computer-executable instructions 1510 maybe executed on one or more of the at least one computing device. Forexample, the computing device 1502 may implement the computer-executableinstructions 1510 and output a result to (and/or receive data from) thecomputing device 1504. Since the computing device 1502 may be wholly orpartially contained within the computing device 1504, the device 1504also may be said to execute some or all of the computer-executableinstructions 1510, in order to be caused to perform or implement, forexample, various ones of the techniques described herein, or othertechniques.

The device 1504 may include, for example, a portable computing device,workstation, or desktop computing device. In another example embodiment,the computing device 1502 is operable to communicate with the device1504 associated with the user 1512 to receive information about theinput from the user 1512 for performing data access and data processing,and assign a unique identifier at least partly based on thedevice-identifier data and the network-participation identifier data.

FIG. 16 illustrates alternative embodiments of the example operationalflow 300 of FIG. 3. FIG. 16 illustrates example embodiments where theaccepting operation 320 may include at least one additional operation.Additional operations may include operation 1600, 1602, and/or operation1604.

Operation 1600 depicts accepting network-participation identifier dataassociated with a verified real-world user associated with the at leastone communication device, further comprising associatingnetwork-participation identifier data with a real-world user associatedwith the at least one communication device. To continue an example ofoperation 302 above in which unique identifier unit 102 and/ornetwork-participation identifier acceptor module 106 may accept fromFacebook a username associated with a verified real-world user having aniPhone and corresponding account with a telecommunications company, theunique identifier unit 102 and/or identity prediction module 122 maysearch one or more identity databases for associations between theusername and a real-world user, and for associations between thatreal-world user and the iPhone. Sources of data for associating a userwith network-participation data and/or a communication device mayinclude, for example, information that is provided by the user. Forexample, social network, message boards, internet forums, and the likemay contain a link between a username and a phone number, a real-worldname, birth date, gender, age, or other identifying attribute. Privatesources of data may also include information provided by the user, suchas private social networks, e-commerce websites, or any websites towhich a consumer provides sign-up information. Publicly availablesources may contain unique consumer information, including for example,vehicle registration records, real estate records, driving records,voting records, political donations, health information, governmentrelated data, technographics, or any other on-line sources disclosinginformation about people. Examples of algorithms that may be employed toperform these associations can be found in U.S. Patent ApplicationPublication 2010/0088313 “Data Source Attribution System,” herebyincorporated in its entirety by reference. See also U.S. PatentApplication Publication 2010/0010993 “Distributed Personal InformationAggregator,” also hereby incorporated in its entirety by reference.

In the example above, the Facebook username may be used as a searchquery by identity prediction module 122 to find the same username on ablog containing a real-world name and mobile phone number associatedwith the username, the mobile phone number being assigned to the iPhoneassociated with the now-verified real-world user associated with theFacebook username.

Operation 1602 depicts associating network-participation identifier datawith a real-world user associated with the at least one communicationdevice, including at least one of performing the association usingidentity prediction, performing the association using de-anonymization,or performing the association using real-name profiling. For example,unique identifier unit 102, identity prediction module 122,de-anonymization module 244, and/or real-name profiling module 246 mayassociate network-participation identifier data with a real-world userassociated with the at least one communication device, including atleast one of performing the association using identity prediction,performing the association using de-anonymization, or performing theassociation using real-name profiling. For example, accept from LinkedInthe name of a person associated with a videoconferencing device andcorresponding account with a videoconferencing service such as WebEx Webconferencing. If the association between the LinkedIn subscriber and areal-world user associated with the videoconferencing device is missing,identity prediction module 122 may search relevant identity databasesfor matches to the subscriber's username or other profile data. In thisway, verification of the real-world user can be accomplished, andassociation between the network-participation identifier data and theuser associated with the communications device can be performed.

Operation 1604 depicts associating network-participation identifier datawith a real-world user associated with the at least one communicationdevice, including at least one of performing the association using webhistory tracking, performing the association using media contenttracking, or performing the association using app data tracking. Forexample, unique identifier unit 102, Web history tracking module 248,media content tracking module 250, and/or app data tracking module 252may associate network-participation identifier data with a real-worlduser associated with the at least one communication device, including atleast one of performing the association using web history tracking,performing the association using media content tracking, or performingthe association using app data tracking. For example, unique identifierunit 102 may accept from Google the email address of a person associatedwith an Android phone and corresponding account with a wireless carrier.In this example, app data tracking module 252 may match the emailaddress with device ID from the phone, e.g., SIM data, and make theassociation between the email address and the phone. Additionally, webhistory tracking module 248 may search public databases for verificationthat a real-world user is associated with the email address, for exampleby searching department of motor vehicle records or real estate records.

Regulating Information Flow During Interactions

FIG. 17 illustrates an example system 1700 in which embodiments may beimplemented. The system 1700 includes a persona creation unit 1706. Thepersona creation unit 1706 may contain, for example, personalinformation request acceptor module 1708, which may in turn containidentification request acceptor module 1710, financial informationrequest acceptor module 1712, and/or web page parser module 1714. Webpage parser module 1714 may contain X/Y coordinate web page reader 1716,web page image reader 1718, and/or screen scraper module 1719. Personacreation unit 1706 also may contain, for example, transaction analysislogic 1730 and/or persona compiler module 1720, which may in turncontain personal information anonymizer module 1722, persona creationruleset module 1724, vendor-specific persona database 1726, and/orpersonal assistant-mediated persona compiler module 1728. Personacreation unit 1706 may communicate over a network or directly with user1701 to accept indication of interaction 1704 reflecting interaction1702 with interaction partner 1703. Persona creation unit 1706 may alsocommunicate over a network or directly with user 1701 and/or interactionpartner 1703 to present persona 1740.

In FIG. 17, persona creation unit 1706 may accept indication ofinteraction 1704 by direct inspection of interaction 1702 or from user1701 and/or interaction partner 1703. Optionally, persona creation unit1706 may accept indication of interaction 1704 such as a request forpersonal information, a transaction indication, and/or a call from user1701 for a persona.

In FIG. 17, the persona creation unit 1706 is illustrated as possiblybeing included within a system 1700. Of course, virtually any kind ofcomputing device may be used to implement the special purpose personacreation unit 1706, such as, for example, a workstation, a desktopcomputer, a networked computer, a server, a collection of servers and/ordatabases, a virtual machine running inside a computing device, a mobilecomputing device, or a tablet PC.

Additionally, not all of the persona creation unit 1706 need beimplemented on a single computing device. For example, the personacreation unit 1706 may be implemented and/or operable on a remotecomputer, while a user interface and/or local instance of the personacreation unit 1706 are implemented and/or occur on a local computer.Further, aspects of the persona creation unit 1706 may be implemented indifferent combinations and implementations than that shown in FIG. 17.For example, functionality of a user interface may be incorporated intothe persona creation unit 1706. The persona creation unit 1706 mayperform simple data relay functions and/or complex data analysis,including, for example, fuzzy logic and/or traditional logic steps.Further, many methods of establishing different online personasdescribed herein or known in the art may be used, including, forexample, algorithms commonly used in web page analysis may be used todetermine a transaction scale as a basis for creating an appropriatepersona containing an appropriate level of personal information for thattransaction. In some embodiments, the persona creation unit 1706 maycreate a persona based on indications of interaction available asupdates through a network.

Persona creation unit 1706 may access data stored in virtually any typeof memory that is able to store and/or provide access to information in,for example, a one-to-many, many-to-one, and/or many-to-manyrelationship. Such a memory may include, for example, a relationaldatabase and/or an object-oriented database, examples of which areprovided in more detail herein.

As referenced herein, the persona creation unit 1706 may be used toperform various data querying and/or recall techniques with respect tothe indication of interaction 1704 and/or the interaction 1702, in orderto create and present an appropriate persona 1740. For example, whereindication of interaction 1704 elements are organized, keyed to, and/orotherwise accessible using one or more web page analysis tools, or thelike, persona creation unit 1706 may employ various Boolean,statistical, and/or semi-boolean searching techniques to determine theappropriate level of information to place in a persona to be created.Similarly, for example, where user personal information is organized,keyed to, and/or otherwise accessible using one or more persona creationrulesets, various Boolean, statistical, and/or semi-boolean searchingtechniques may be performed by persona creation unit 1706 to create anappropriate persona.

Many examples of databases and database structures may be used inconnection with the persona creation unit 1706. Such examples includehierarchical models (in which data is organized in a tree and/orparent-child node structure), network models (based on set theory, andin which multi-parent structures per child node are supported), orobject/relational models (combining the relational model with theobject-oriented model).

Still other examples include various types of eXtensible Mark-upLanguage (XML) databases. For example, a database may be included thatholds data in some format other than XML, but that is associated with anXML interface for accessing the database using XML. As another example,a database may store XML data directly. Additionally, or alternatively,virtually any semi-structured database may be used, so that context maybe provided to/associated with stored data elements (either encoded withthe data elements, or encoded externally to the data elements), so thatdata storage and/or access may be facilitated.

Such databases, and/or other memory storage techniques, may be writtenand/or implemented using various programming or coding languages. Forexample, object-oriented database management systems may be written inprogramming languages such as, for example, C++ or Java. Relationaland/or object/relational models may make use of database languages, suchas, for example, the structured query language (SQL), which may be used,for example, for interactive negotiation of persona content and/or forgathering and/or compiling data from the relational database(s).

For example, SQL or SQL-like operations over one or more indications ofinteraction 1704 and/or interaction 1702 may be performed, or Booleanoperations using indications of interaction 1704 and/or interaction 1702may be performed. For example, weighted Boolean operations may beperformed in which different weights or priorities are assigned to oneor more of the indications of interaction 1704 and/or interaction 1702,including various transaction identifier elements, locations, and/orcontexts, perhaps relative to one another. For example, anumber-weighted, exclusive-OR operation may be performed to requestspecific weightings of elements found on a check-out page of ane-commerce web page (e.g., dollar amount in cart, web site name, paymenttype).

Following are a series of flowcharts depicting implementations. For easeof understanding, the flowcharts are organized such that the initialflowcharts present implementations via an example implementation andthereafter the following flowcharts present alternate implementationsand/or expansions of the initial flowchart(s) as either sub-componentoperations or additional component operations building on one or moreearlier-presented flowcharts. Those having skill in the art willappreciate that the style of presentation utilized herein (e.g.,beginning with a presentation of a flowchart presenting an exampleimplementation and thereafter providing additions to and/or furtherdetails in subsequent flowcharts) generally allows for a rapid and easyunderstanding of the various process implementations. In addition, thoseskilled in the art will further appreciate that the style ofpresentation used herein also lends itself well to modular and/orobject-oriented program design paradigms.

FIG. 18 illustrates an operational flow 1800 representing exampleoperations related to regulating information flow during interactions.In FIG. 18 and in following figures that include various examples ofoperational flows, discussion and explanation may be provided withrespect to the above-described system environments of FIG. 17, and/orwith respect to other examples and contexts. However, it should beunderstood that the operational flows may be executed in a number ofother environments and contexts including that of FIG. 26, and/or inmodified versions of FIG. 17. Also, although the various operationalflows are presented in the sequence(s) illustrated, it should beunderstood that the various operations may be performed in other ordersthan those which are illustrated, or may be performed concurrently.

After a start operation, operation 1810 depicts accepting at least oneindication of an interaction involving at least one member of a network.For example, persona creation unit 1706, personal information requestacceptor module 1708, and/or persona compiler module 1720 may acceptindication of interaction 1704 from a user 1701, for example in the formof auction bid dollar amount, a website name, or a purchase item name ordollar value. In another example, persona creation unit 1706 ortransaction analysis logic 1730 may accept markup language code (e.g.,HTML or XML) corresponding to a web page as the indication ofinteraction 1704.

Operation 1820 depicts creating a persona corresponding to the at leastone member of a network, wherein the persona is at least partly based onthe indication of an interaction. For example, persona creation unit1706, personal information request acceptor module 1708, and/or personacompiler module 1720 may create a persona corresponding to the at leastone member of a network, wherein the persona is at least partly based onthe indication of an interaction. In one embodiment, persona creationunit 1706 may accept markup language code from a checkout webpage as theindication of interaction 1704. In this example, the code may indicate adollar value of a purchase or auction bid. Based on that dollar value,the persona compiler module 1720 may present a specific personacontaining specific personal information about the user for use in theinteraction. In some embodiments, persona compiler 1720 may present alimited persona or alias of the user where the interaction is deemed bypersona creation unit 1706 and/or transaction analysis logic 1730 to beof low dollar value. For financial interactions such as purchases orauctions, transaction analysis logic 1730 may detect a dollar value andassign a dollar value category for the interaction, for example lowdollar value, intermediate dollar value, or high dollar value.

Alternatively, many intermediate levels of interaction value may beassigned based on a detected value present in the code or otherattribute of the interaction. In these embodiments, a minimal personacontaining few elements of personal information may be presented. Incases where a negotiation is initiated, subsequent presentations ofpersonas containing progressively more personal information may bepresented with the goal that an acceptable persona may be presented tothe interaction partner which provides only that amount of personalinformation which is sufficient for completion of theinteraction/transaction. This approach attempts to avoid gratuitousdissemination of potentially valuable personal information. For example,for low dollar transactions, persona compiler logic 1720 may beprogrammed to put together a persona for the user 1701 containing only aname and a device identifier, such as a telephone number. For someinteraction partners, such a minimal persona will provide enough trustin the credit-worthiness of the user 1701, perhaps via a check with atelecommunications carrier that the name matches the telephone number.In other, higher dollar value transactions, a persona containing moredetailed personal information may be necessary. For example, for a carpurchase, a persona including credit information, credit history, andpersonal financial asset data may be presented by persona compiler logic1720.

In some embodiments, user 1701 will provide indication of interaction1704 to persona creation unit 1706. In another embodiment, user 1701 maygrant access to interaction 1702, for example by an affirmative step ofopting-in or by not opting-out of a request by persona creation unit1706. Personal information may be obtainable as a matter of course bypersona creation unit 1706. For example, personal information of a user1701 may be directly entered into persona creation unit 1706 for thepurpose of allowing the unit to create personas, or alternatively,persona creation unit 1706 may indirectly access personal informationthrough access to various accounts of user 1701, such as bank accounts,social network accounts, or telecommunications accounts. In someembodiments, some of the personal information may be publicly available.

Operation 1830 depicts presenting the persona for use in the interactioninvolving the at least one member of the network. For example, personacreation unit 1706, upon creating a persona based on an indication ofinteraction 1704, may present the persona for use in the interactioninvolving the at least one member of the network. For example, personacreation unit 1706 may accept a request for personal information from aninteraction partner such as amazon.com. Persona creation unit 1706 maythen assess the interaction 1702 based on dollar amount or personalinformation requested, and create a persona accordingly, perhapsaccording to a persona creation ruleset pre-programmed into personacreation ruleset module 1724. Persona creation unit 1706 may thenpresent the persona to user 1701 for use in interaction 1702, ordirectly present the persona to the interaction 1702, perhaps in theform of filling in personal information fields on an e-commerce website.Such fields are equivalent to requests for personal information.

In some embodiments, persona creation unit 1706 may include a personacompiler algorithm such as an anonymization algorithm, a user-definedpersona creation algorithm (i.e., ruleset), a vendor-specific personacreation algorithm, and/or a personal assistant-mediated personacompiler algorithm. These algorithms may aid in the creation of personasthat are appropriate to a given interaction 1702.

In some embodiments, both for detecting the specifics of an interactionor transaction on a web page and for placing data into fields on a webpage, it may be useful to perform web scraping or web page imageanalysis on the web page.

Web scraping is a computer software technique of extracting informationfrom websites. Usually, such software programs simulate humanexploration of the World Wide Web by either implementing low-levelHypertext Transfer Protocol (HTTP), or embedding certain full-fledgedWeb browsers, such as Internet Explorer or Mozilla Firefox. Web scrapingmay involve the transformation of unstructured data on the Web,typically in HTML format, into structured data that can be stored andanalyzed in a central local database or spreadsheet. Specific techniquesfor web scraping include text grepping and regular expression matching,which extracts information from Web pages based on the UNIX grep commandor regular expression matching facilities of programming languages (forinstance Perl or Python).

Another web scraping tool is HTTP programming wherein static and dynamicweb pages can be retrieved by posting HTTP requests to a remote webserver using socket programming.

Another web scraping tool is DOM (document object model) parsing: Byembedding a full-fledged web browser, such as Internet Explorer orMozilla web browser, programs can retrieve dynamic content generated byclient-side scripts. These web browser controls may also parse web pagesinto a DOM tree, based on which programs can retrieve parts of the webpages.

Another web scraping tool is HTML parsing, wherein semi-structured dataquery languages, such as XQuery and HTQL can be used to parse HTML pagesand to retrieve and transform web content.

There are many web-scraping software tools available that can be used tocustomize web-scraping solutions. These programs may attempt toautomatically recognize the data structure of a page or provide a webrecording interface that removes the necessity to manually writeweb-scraping code, or some scripting functions that can be used toextract and transform web content, and database interfaces that canstore the scraped data in local databases.

Another web scraping tool is a vertical aggregation platform. Theseplatforms create and monitor a multitude of “bots” for specificverticals with no man-in-the-loop, and no work related to a specifictarget site. The preparation involves establishing a knowledge base forthe entire vertical, and then the platform creates the botsautomatically. The platform's robustness is measured by the quality ofthe information it retrieves (usually number of fields) and itsscalability (how quick it can scale up to hundreds or thousands ofsites). This scalability is mostly used to target sites that commonaggregators find complicated or too labor intensive to harvest contentfrom.

Another web scraping tool is semantic annotation recognizing, whereinweb pages may contain metadata or semantic markups/annotations which canbe made use of to locate specific data. If the annotations are embeddedin the pages, as Microformat does, this technique can be viewed as aspecial case of DOM parsing. In another case, the annotations, organizedinto a semantic layer, may be stored and managed separately from the webpages, so the web scrapers can retrieve data schema and instructionsfrom this layer before scraping the pages.

Another tool for web page analysis is iMacros, a program that harvestsweb data automatically, which can do automatic form-filling. Forexample, iMacros works with every website; even the most complicatedwebsites that use dialog boxes, frames, Javascript and AJAX can beautomated. It has high data extraction speed: on a typical computer,20-50 instances of iMacros can be run at once (“multi-threading”). Ithas full web-crawling support. iMacros can be scheduled to run in thebackground of other programs or in lean traffic hours. iMacros permitschange of IP addresses programmatically with full PROXY support. Afterharvesting the web data, actions may be performed on it, it can betransferred to any application, or it can be used in another process.iMacros integrates with every Windows scripting or programming language.iMacros can connect to any database or software application. iMacrosprovides visual recording of all web activities and the extractionmacros. iMacros has full unicode support, and iMacros can extract textin all languages, including Asian languages such as Chinese, Japaneseand Korean.

In addition to working with the website source code like a “normal”software program, iMacros can also look at the website like a humandoes: iMacros' image recognition support allows a user to automate andtest websites using images instead of X/Y coordinates: a user can telliMacros what a button looks like and iMacros can find it on the page.Even when the button has moved or if it has changed color or screenresolution. The iMacros Image Recognition Wizard functions with websites that use non-HTML technologies such as Flash applets, Javaapplets, Movie Player Applets, ActiveX controls or any other technology.Since the software relies only on the images that are rendered in thebrowser, it works independently of the underlying technology.

The creation of personas described and claimed herein may function as acontrol feature of the unique identifier described above. In oneembodiment, cascaded personas give more and more access to yourreal-world assets information. These personas may be uniquely orsemi-uniquely linked to a real user. A credit bank such as Visa maymanages these online personas—from something with little personalinformation such as “white male” to detailed real-life identityinformation. Because there is a direct link to personal information,provided by a telecommunications carrier via the device, it is possibleto protect previously vulnerable web surfers who are at risk for havingtheir personal information taken at will by snoopers. A user may lookonline and find a persona on the internet that is uniquely associatedwith them.

Under the persona creation environment described herein, opt-in may nolonger be binary because a user may opt in to a set of circumstancesaround a persona or a type of identification. In this environment a userwill have a true identity—SIM data and all that goes with it—that may ormay not be communicated to an interaction partner 1703 depending uponthe nature of interaction 1702. Accordingly, in the herein envisionedpersonas/relationships a user may have an unfolding level of envelopesthat increases exposure to their personal information as you go deeperinto the value of an interaction.

In one embodiment, a user interface with persona creation unit 1706 willspecify—easily and preferably visually—exactly what type of commercialobligations and/or identity personas/relationships he/she is enteringwhen he/she consents to assume a particular persona template.

FIG. 19 illustrates alternative embodiments of the example operationalflow 1800 of FIG. 18. FIG. 19 illustrates example embodiments where theaccepting operation 1810 may include at least one additional operation.Additional operations may include operation 1900, 1902, 1904, and/oroperation 1906.

Operation 1900 depicts accepting from at least one member of a networkan indication of an interaction involving the at least one member of anetwork. For example, persona creation unit 1706 and/or personalinformation request acceptor module 1708 may accept from user 1701 anindication of interaction 1704 such as a request for a persona to giveto iTunes for the purchase of an MP3 file. As another example, personalinformation request acceptor module 1708 may forward from user 1701 arequest for personal information from an e-commerce website such asGroupon relating to a potential purchase. In some embodiments, user 1701may send a message to persona creation unit 1706 telling it that aninteraction requiring a persona is happening, the message including aURL or other venue for the interaction, from which persona creation unit1706 can extract the information necessary to evaluate the interactionand create an appropriate persona. Such a message may be sent by voice,text, touch, or other user interface mechanism.

Operation 1902 depicts accepting from an eBay user an indication ofinterest in an online auction. For example, persona creation unit 1706and/or personal information request acceptor module 1708 may accept fromuser 1701 an indication of interest in an online auction. For example,personal information request acceptor module 1708 may accept a URL foran eBay auction page as the indication of interest in an online auction.Alternatively, eBay user 1701 may provide to persona creation unit 1706a URL for an eBay auction page, and a URL for an eBay sign in pagehaving fields for a User ID and Password as the indication of interestin an online auction.

Operation 1904 depicts accepting a request for personal information asthe at least one indication of an interaction involving at least onemember of a network. For example, persona creation unit 1706 and/orpersonal information request acceptor module 1708 may accept a requestfor personal information as the at least one indication of aninteraction involving at least one member of a network. In oneembodiment, personal information request acceptor module 1708 may accepta request for personal information on an e-commerce sign up page, suchas name, address, email address, or credit card information. The requestfor personal information may be in the form of field on a web page,perhaps bearing an asterisk indicating required personal information, orappearing in red type indicating required personal information. Inanother embodiment, a request for personal information may be in theform of a field(s) asking for a shipping address.

Operation 1906 depicts accepting a request for at least one of name,physical address, email address, phone number, or credit cardinformation as the personal information. For example, persona creationunit 1706 and/or personal information request acceptor module 1708 mayaccept a request for at least one of name, physical address, emailaddress, phone number, or credit card information as the personalinformation. In one embodiment, personal information request acceptormodule 1708 may accept a request for personal information on ane-commerce check out page, such as name, address, email address, orcredit card information. For example, identification request acceptormodule 1710 may accept a request for a user name and password from ane-commerce website such as Amazon.com or iTunes.

FIG. 20 illustrates alternative embodiments of the example operationalflow 1800 of FIG. 18. FIG. 20 illustrates example embodiments where theaccepting operation 1810 may include at least one additional operation.Additional operations may include operation 2000, 2002, 2004, 2006,2008, and/or operation 2010.

Operation 2000 depicts accepting an indication of an online transactioninvolving at least one member of a network. For example, personacreation unit 1706, identification request acceptor module 1710, and/orfinancial information request acceptor module 1712 may accept anindication of an online transaction involving at least one member of anetwork. For example, identification request acceptor module 1710 mayanalyze a URL provided by a user 1701 corresponding to a social networksign up page such as the Facebook sign up page (e.g.,http://www.facebook.com) having fields for first name, last name, emailaddress, gender, age and password. In another example, web page parsermodule 1714 may accept a URL for a sign-in page, such as the sign-inpage for Google mobile (e.g., m.google.com), and parse the markuplanguage code to identify fields requesting a username and password.Other embodiments may involve transactions that are financial, asdiscussed below.

Operation 2002 depicts accepting an indication of an online financialtransaction involving at least one member of a network. For example,persona creation unit 1706 and/or financial information request acceptormodule 1712 may accept an indication of an online financial transactioninvolving at least one member of a network. In one embodiment, financialinformation request acceptor module 1712 may accept a request for aneBay user's PayPal account information as the indication of an onlinetransaction involving at least one member of a network. In anotherembodiment, financial information request acceptor module 1712 mayaccept a request for an iTunes user's credit card information as theindication of an online transaction involving at least one member of anetwork. In another embodiment, financial information request acceptormodule 1712 may accept a request for an Amazon.com user's credit cardinformation as the indication of an online transaction involving atleast one member of a network.

Operation 2004 depicts accepting an indication of at least one of asign-up page, a login page, or a checkout page involving at least onemember of a network. For example, persona creation unit 1706,identification request acceptor module 1710, financial informationrequest acceptor module 1712, and/or web page parser module 1714 mayaccept an indication of at least one of a sign-up page, a login page, ora checkout page involving at least one member of a network. In oneembodiment, financial information request acceptor module 1712 mayaccept a login page request for information from a member of the AmazonPrime network. In another example as discussed above, web page parsermodule 1714 may accept a URL for a sign-in page, such as the sign-inpage for Google mobile (e.g., m.google.com), and parse the markuplanguage code to identify fields requesting a username and password.

Operation 2006 depicts accepting an indication of an interactioninvolving at least one member of a social network. For example, personacreation unit 1706, identification request acceptor module 1710, and/orfinancial information request acceptor module 1712 may accept anindication of an interaction involving at least one member of a socialnetwork. For example as discussed above, identification request acceptormodule 1710 may analyze a URL provided by a user 1701 corresponding to asocial network sign up page such as the Facebook sign up page (e.g.,http://www.facebook.com) having fields for first name, last name, emailaddress, gender, age and password. In another example, web page parsermodule 1714 may accept a URL for a sign-in page, such as the sign-inpage for Google+ (e.g., plus.google.com), and parse the markup languagecode of the sign-in page to identify fields requesting a username andpassword.

Operation 2008 depicts accepting an indication of an interaction betweena registered member of a commercial website and the commercial website.For example, persona creation unit 1706, identification request acceptormodule 1710, and/or financial information request acceptor module 1712may accept an indication of an interaction between a registered memberof a commercial website and the commercial website. In one embodiment,financial information request acceptor module 1712 may accept a requestfor a registered eBay user's PayPal account information in aninteraction between the registered eBay user and the eBay website. Inanother embodiment, financial information request acceptor module 1712may accept a request for a registered member of iTunes' credit cardinformation in an interaction between the registered iTunes user and theiTunes website. In another embodiment, financial information requestacceptor module 1712 may accept a request for information fromamazon.com during a transaction between a member of Amazon Prime and theamazon.com website.

Operation 2010 depicts accepting an indication of an interaction betweena registered member of amazon.com and the amazon.com website. Forexample, persona creation unit 1706, identification request acceptormodule 1710, and/or financial information request acceptor module 1712may accept an indication of an interaction between a registered memberof amazon.com and the amazon.com website. In one embodiment, financialinformation request acceptor module 1712 may accept a request forinformation from Amazon.com during a transaction between a registeredmember of amazon.com and the amazon.com website, perhaps at the sign-inpage on which the web page has fields for, e.g., username and password.

FIG. 21 illustrates alternative embodiments of the example operationalflow 1800 of FIG. 18. FIG. 21 illustrates example embodiments where thecreating operation 1820 may include at least one additional operation.Additional operations may include operation 2100 and/or operation 2102.

Operation 2100 depicts creating a set of personal informationcorresponding to the at least one member of a network, wherein the setof personal information is at least partly based on the indication of aninteraction. For example, persona creation unit 1706 and/or personacompiler module 1720 may create a set of personal informationcorresponding to the at least one member of a network, wherein the setof personal information is at least partly based on the indication of aninteraction. In one embodiment, persona creation unit 1706, havingaccepted an indication of interaction 1704 may compile a set of personalinformation for user 1701 to use in the interaction 1702. The set ofpersonal information may be commensurate with the scale of theinteraction. A general rule to protect personal information frompossible identity thieves, advertisers, and spammers is to reveal aslittle personal information as possible within the requirements of theinteraction.

As discussed above, individuals commonly have large amounts of personalinformation online that is publicly available, leaving them open toprofiling by advertisers and those with even less honorable intentionssuch as identity thieves. Accordingly, as a way of mitigating the riskof spam and identity theft, it will be desirable for those interactingwith websites to limit the dissemination of personal information,particularly when an interaction or transaction does not absolutelyrequire transfer of certain personal information. For example, lowdollar value online transactions ought not require detailed personalinformation about the buyer. If sufficient trust in payment isavailable, for example via an anonymous telecommunications carrieraccount, unique identifier as discussed above, or device identifier assecurity for the transaction, that ought to suffice. Conversely, highdollar value transactions will still require that detailed personalinformation be provided as security for the transaction, but a largerange of intermediate dollar value transactions may benefit from a smartsystem of providing as little personal information possible during thetransaction.

Operation 2102 depicts creating a set of anonymized personal informationcorresponding to the at least one member of a network, wherein the setof anonymized personal information is at least partly based on theindication of an interaction. For example, persona creation unit 1706,persona compiler module 1720, and/or personal information anonymizermodule 1722 may create a set of anonymized personal informationcorresponding to the at least one member of a network, wherein the setof anonymized personal information is at least partly based on theindication of an interaction. In one embodiment, personal informationanonymizer module 1722 may, for a low dollar value transaction, createan anonymized set of personal information for user 1701 to use in buyinga staple object online. This may provide for anonymous private salesonline, in which the security of the transaction for the seller isprovided by, for example, a Verizon account number associated with amobile device on which the transaction is taking place. In someembodiments, such an account number may be associated with an alias forthe actual account holder to enhance privacy in the transaction.

In some embodiments, user 1701 may want to have multiple aliases, eachhaving a different amount of personal information detail as appropriatefor use in various online activities.

FIG. 22 illustrates alternative embodiments of the example operationalflow 1800 of FIG. 18. FIG. 22 illustrates example embodiments where thecreating operation 1820 may include at least one additional operation.Additional operations may include operation 2200, 2202, 2204, and/oroperation 2206.

Operation 2200 depicts creating a persona corresponding to the at leastone member of a network, wherein the persona is at least partly based onthe indication of an interaction and at least partly based on apersona-creation ruleset. For example, persona creation unit 1706,persona compiler module 1720, and/or persona creation ruleset module maycreate a persona corresponding to the at least one member of a network,wherein the persona is at least partly based on the indication of aninteraction and at least partly based on a persona-creation ruleset. Inone embodiment, persona compiler module 1720, having accepted anindication of interaction 1704 may access persona creation rulesetmodule 1724 to find out whether the indication of interaction 1704matches a predefined rule. For example, persona creation ruleset module1724 may contain a rule stating that online purchases for items having avalue of 25 dollars or less should automatically trigger the creationand presentation of a persona for user 1701 that includes only a nameand necessary payment information, such as an Entropay prepaid virtualVisa card number. In some cases, the name may be an alias, especially incases where using an alias comports with the terms of service of avendor's website.

Operation 2202 depicts creating a persona corresponding to the at leastone member of a network, wherein the persona is at least partly based onthe indication of an interaction and at least one ruleset definingthresholds for assigning personal information to a persona. For example,persona creation unit 1706, persona compiler module 1720, and/or personacreation ruleset module may create a persona corresponding to the atleast one member of a network, wherein the persona is at least partlybased on the indication of an interaction and at least one rulesetdefining thresholds for assigning personal information to a persona. Inone embodiment, persona compiler module 1720, having accepted anindication of interaction 1704 may access persona creation rulesetmodule 1724 to find out whether the indication of interaction 1704matches a predefined rule establishing a threshold. For example, personacreation ruleset module 1724 may contain a rule stating that onlinepurchases for items under 5 dollars in value using virtual currency orcredit may be made using “persona A,” whereas online purchases for itemsthat are 5 dollars to 50 dollars in value using virtual currency orcredit may be made using “persona B.” Personas A and B may differ in,for example, the amount of personal information provided, the virtualaccount to be accessed for payment.

Operation 2204 depicts creating a persona corresponding to the at leastone member of a network, wherein the persona is at least partly based onthe indication of an interaction and at least one ruleset definingdollar amount thresholds for assigning personal information to apersona. For example, persona creation unit 1706, persona compilermodule 1720, and/or persona creation ruleset module may create a personacorresponding to the at least one member of a network, wherein thepersona is at least partly based on the indication of an interaction andat least one ruleset defining dollar amount thresholds for assigningpersonal information to a persona. In one embodiment, persona compilermodule 1720, having accepted an indication of interaction 1704 mayaccess persona creation ruleset module 1724 to find out whether theindication of interaction 1704 matches a predefined rule establishing adollar amount threshold. As in the previous example, persona creationruleset module 1724 may contain a rule stating that online purchases foritems having a value of 25 dollars or less should automatically triggerthe creation and presentation of a persona for user 1701 that includesonly a name and necessary payment information, such as an Entropayprepaid virtual Visa card number. A dollar value threshold may alsoinclude a range, for example, transactions between 1,000 and 5,000dollars in value. In this case, persona compiler module 1720 may consulta rule in persona creation ruleset module 1724 that assigns name,telephone number, physical address, and credit card information to thepersona to be presented. The ruleset may also specify that the creditcard information to be included in the persona should be checked toconfirm that the available credit line is higher than the dollar valueof the transaction, so as to avoid having the credit card declined.

Operation 2206 depicts creating a persona corresponding to the at leastone member of a network, wherein the persona is at least partly based onthe indication of an interaction and at least one ruleset definingthresholds for assigning personal information to a persona at leastpartly based on a context of the interaction. For example, personacreation unit 1706, persona compiler module 1720, and/or personacreation ruleset module may create a persona corresponding to the atleast one member of a network, wherein the persona is at least partlybased on the indication of an interaction and at least one rulesetdefining thresholds for assigning personal information to a persona atleast partly based on a context of the interaction. In one embodiment,persona compiler module 1720, having accepted a request for a “check-in”from a social networking app such as foursquare as the indication ofinteraction 1704 may access persona creation ruleset module 1724 to findout which persona to use in going forward with the check-in. In thisexample, some users may set as a rule using an alias as their personafor checking in geographically if they do not want everyone in theirsocial graph knowing that they are checking in at a certain location.This would allow the user to check in, but in a way that iscontext-sensitive. Similarly, the context of a specific website could bea rule to use a certain persona on that website. For example, differentpersonas could be pre-configured for websites such as amazon.com, eBay,and iTunes. When persona creation unit 1706 accepts data indicating aninteraction with one of these websites, amazon.com, e.g., personacreation unit 1706 may consult persona creation ruleset module 1724 tocall out a pre-programmed persona for use with a transaction on theamazon.com website. The context can be even more detailed by addingother contexts such as dollar value context, time of day context, and/ordevice context. For example, if a user 1701 shares a device like a smartphone with family members and has a shared e-commerce account on, e.g.,eBay, persona creation unit 1706 may detect the smart phone, consultpersona creation ruleset module 1724 to find a ruleset for that smartphone, and apply the appropriate persona. In this example, a parent mayplace an upper limit on all transactions made from the device so as toprevent a child from buying something that is too expensive. Thiscontrol may be manifested by persona creation unit 1706 creating andpresenting a persona for use with eBay on the smart phone which isassociated with a payment means such as a credit card or PayPal accounthaving the desired upper limit.

FIG. 23 illustrates alternative embodiments of the example operationalflow 1800 of FIG. 18. FIG. 23 illustrates example embodiments where thecreating operation 1820 may include at least one additional operation.Additional operations may include operation 2300, 2302, 2304, and/oroperation 2306.

Operation 2300 depicts creating a minimal set of personal informationcorresponding to the at least one member of a network, wherein theminimal set of personal information is at least partly based on theindication of an interaction. For example, persona creation unit 1706and/or personal information anonymizer module 1722 may create a minimalset of personal information corresponding to the at least one member ofa network, wherein the minimal set of personal information is at leastpartly based on the indication of an interaction. For example, personacreation unit 1706 may accept from user 1701 an indication ofinteraction 1704 in the form of a web address linking to a page for thepurchase of a music cd on the bestbuy.com website. In some embodiments,as a default setting, persona creation module 1706 may monitor the webpages visited by a member of a network, e.g., user 1701, and identifylikely web pages or interactions 1702 in which a persona would beuseful. For example, if persona creation module 1706 has access to theweb pages visited by user 1701, it can examine the code of those pageslooking for telltale signs of an e-commerce transaction or othertransaction in which a persona could be useful. Such telltale signs mayinclude words associated with a purchase such as payment type, creditcard type, dollar amount, “cart,” “buy now,” tax, shipping, or the like.Alternatively, telltale signs may include personal informationcategories that typically appear on sign-up or sign-in pages such asname, username, password, and email address. In the above example, for aminor purchase such as a music cd or mp3, personal informationanonymizer module 1722 may anonymize certain personal information ofuser 1701 under the theory that bestbuy.com does not need very muchpersonal information to be assured of payment for the music. Assuranceof payment may be obtained from, for example, a telecommunicationscarrier, credit card account, or virtual payment.

Operation 2302 depicts creating a persona including name, physicaladdress, and device identifier data corresponding to the at least onemember of a network, wherein the persona is at least partly based on anindication of a low-dollar-cost transaction. For example, personacreation unit 1706 and/or personal information anonymizer module 1722may create a persona including name, physical address, and deviceidentifier data corresponding to the at least one member of a network,wherein the persona is at least partly based on an indication of alow-dollar-cost transaction. For example, persona creation unit 1706 mayaccept from user 1701 an indication of interaction 1704 in the form of acheck-out page having fields for payment including credit cardinformation, where the dollar amount is under ten dollars. For example,in a low-dollar-cost transaction, persona creation unit 1706 may provideonly name, physical address, and device identifier data in satisfyingsecurity concerns of the vendor. In one embodiment, payment may besecured through the telecommunications carrier associated with thedevice identifier data (e.g., SIM data, MEID, or other device identifierdiscussed above). In another embodiment, payment may be secured througha credit card account held by the telecommunications carrier associatedwith the device identifier data. In yet another embodiment, payment maybe secured through a service like Portapayments, which creates quickresponse (QR) codes for PayPal payments. Scanning one of their QR codeswith a mobile device takes a user 1701 to PayPal with the recipient andamount of the transaction automatically filled out. The user 1701 needonly approve the payment to complete the interaction. PortaPaymentsallows customers to purchase goods by scanning a 3D bar code with theirphone. Two types of codes are available: one is free and requires theuse of PortaPayments' application to scan and pay; the other, called auniversal code, has a fee associated with it and will work with any QRcode scanner that can scan and direct users to website URLs.

Operation 2304 depicts creating a detailed set of personal informationcorresponding to the at least one member of a network, wherein thedetailed set of personal information is at least partly based on theindication of an interaction. In one example, persona creation unit 1706may create a detailed set of personal information corresponding to theat least one member of a network, wherein the detailed set of personalinformation is at least partly based on the indication of aninteraction. For example, persona creation unit 1706 may accept anindication of interaction 1704 in the form of an e-commerce cart websiteon which is shown an item to be purchased having a price of 1500dollars. The interaction partner 1703 in this transaction may require arelatively detailed set of personal information before approving thesale. For example, to circumvent fraud, personal information including acredit card number (perhaps with a card security code), valid emailaddress, name matching that on the card, and physical address matchingthe billing address of the credit card.

Operation 2306 depicts creating a persona including real name, physicaladdress, credit card information, and device identifier informationcorresponding to the at least one member of a network, wherein thepersona is at least partly based on an indication of a high-dollar-costtransaction. In one example, persona creation unit 1706 may create apersona including real name, physical address, credit card information,and device identifier information corresponding to the at least onemember of a network, wherein the persona is at least partly based on anindication of a high-dollar-cost transaction. To continue the aboveexample, persona creation unit 1706 may accept an indication ofinteraction 1704 in the form of an e-commerce cart website on which isshown an item to be purchased having a price of 1500 dollars. Theinteraction partner 1703 in this transaction may require a relativelydetailed set of personal information before approving the sale. Forexample, personal information including a credit card number (perhapswith a card security code), valid email address, name matching that onthe card, and physical address matching the billing address of thecredit card. However, persona creation unit 1706 may also include deviceidentifier information, perhaps in lieu of other elements of personalinformation. In some embodiments, device identifier information incombination with other personal information such as telecommunicationsaccount number may provide security for payment to the vendor, perhapseven to the extent that a credit card number is not necessary where thetelecommunications carrier stands in as the guarantor for the value ofthe transaction.

FIG. 24 illustrates alternative embodiments of the example operationalflow 1800 of FIG. 18. FIG. 24 illustrates example embodiments where thepresenting operation 1830 may include at least one additional operation.Additional operations may include operation 2400, 2402, 2404, 2406,and/or operation 2408.

Operation 2400 depicts placing elements of the persona into fields of anonline form for use in the interaction involving the at least one memberof the network. In one example, persona creation unit 1706 and/orvendor-specific persona database 1726 may create a persona for user 1701based on an interaction 1702 with an amazon.com checkout page. Uponapproval by the user 1701, the individual information elements of thecreated persona may be placed in the appropriate fields/boxes on theamazon.com checkout web page. This may be facilitated by vendor-specificpersona database 1726, which may, in addition to having informationabout what personal information is required, may contain information asto where on the checkout page various personal information should go,perhaps in the form of markup language code, ordinary web page text, orXY coordinates, for example.

Operation 2402 depicts presenting the persona to an online vendor foruse in securing credit for an online purchase from the online vendor. Inone example, persona creation unit 1706 may present the persona to anonline vendor for use in securing credit for an online purchase from theonline vendor. To continue the embodiment above, persona creation unit1706 may create a persona for user 1701 based on an interaction 1702with an amazon.com checkout page as the interaction partner 1703. Inthis example user 1701 may be a member of the Amazon Prime network,Facebook, or the hotmail email network. In some embodiments, membershipin the network may help secure low-dollar-value transactions. Morespecifically, verified membership in an exclusive private network suchas Sermo for physicians or LinkedIn for professionals may suffice assecurity for low-dollar-value transactions, perhaps with only name andemail address in addition.

Operation 2404 depicts presenting the persona at a vendor's physicalestablishment for use in securing credit for a purchase from the vendor.In one example, persona creation unit 1706 may present the persona at avendor's physical establishment for use in securing credit for apurchase from the vendor. In one embodiment, a mobile device having apersona creation unit 1706 (either on the client or on a server perhapsas a cloud service) may be used to broker a transaction for a user 1701at a device reader at a physical location of an interaction partner1703. In this example, a vendor equipped with a near fieldcommunications reader may use the reader to communicate with thereader's device to exchange details of a purchase and a created persona.For example, for low-dollar-value purchases, a persona associated with aGoogle wallet account, even if the vendor's terminal is not PayPassenabled. For some transactions, the Google wallet account-associatedpersona may suffice as security for the transaction, perhaps through atransfer of virtual currency or credit. Another example of this mayemploy a persona associated with the Entropay prepaid virtual credittechnology described above.

Operation 2406 depicts presenting the persona via a computer-implementedpersonal assistant for use in the interaction involving the at least onemember of the network. In one example, persona creation unit 1706 maypresent the persona via a computer-implemented personal assistant foruse in the interaction involving the at least one member of the network.In one embodiment, a mobile device having a persona creation unit 1706(either on the client or on a server perhaps as a cloud service) througha personal assistant interface may be used to broker a transaction, suchas an online purchase, for a user 1701. Natural language processing hasadvanced to the point where speech recognition and response by a mobiledevice is able to mediate persona management in the context of atransaction with only minimal input from the user 1702, and that byvoice alone. For example, user 1701 may say to his mobile device “createa persona for buying a New York Times subscription on my iPad.” Thepersona creation unit 1706 may accordingly access the web to find thecost of such a subscription so as to provide a persona with theappropriate amount of personal information. If subscriptions fordifferent time periods are found, the personal assistant may ask user1701 which he is interested in, for example one year. The personalassistant may then present a persona or two to the user 1701, the usermay select one, and then the personal assistant may then open the NewYork Times subscription ordering web page and complete the appropriatefields according to the persona selected. The user may retain finalconfirmation of the purchase by voice command via the personalassistant.

Operation 2408 depicts presenting the persona via a computer-implementedpersonal assistant for use in the interaction involving the at least onemember of the network, wherein Siri is the computer-implemented personalassistant. In one example, persona creation unit 1706 may present thepersona via a computer-implemented personal assistant for use in theinteraction involving the at least one member of the network, whereinSiri is the computer-implemented personal assistant. As described above,a personal assistant may be used at each operation of the claimedsystems and methods. Siri is Apple's personal assistant included for thefirst time in the iPhone 4S. Siri may be used as a persona creation unitas described in the example above, for example to rapidly and easily buyapps from the iTunes App Store. Siri's knowledge of the user 1701'sdevice and telecommunications carrier contract details may be used toquickly and easily secure low-dollar-value transaction credit, such asfor iPad apps, in terms of minimal personas that are linked to knowndevices and accounts for a given user 1701.

FIG. 25 illustrates a partial view of an example article of manufacture2500 that includes a computer program 2504 for executing a computerprocess on a computing device. An embodiment of the example article ofmanufacture 2500 is provided including a signal bearing medium 2502, andmay include one or more instructions for accepting at least oneindication of an interaction involving at least one member of a network;one or more instructions for creating a persona corresponding to the atleast one member of a network, wherein the persona is at least partlybased on the indication of an interaction; and one or more instructionsfor presenting the persona for use in the interaction involving the atleast one member of the network. The one or more instructions may be,for example, computer executable and/or logic-implemented instructions.In one implementation, the signal-bearing medium 2502 may include acomputer-readable medium 2506. In one implementation, the signal bearingmedium 2502 may include a recordable medium 2508. In one implementation,the signal bearing medium 2502 may include a communications medium 2510.

FIG. 26 illustrates an example system 2600 in which embodiments may beimplemented. The system 2600 includes a computing system environment.The system 2600 also illustrates a user 2612 using a device 2604, whichis optionally shown as being in communication with a computing device2602 by way of an optional coupling 2606. The optional coupling 2606 mayrepresent a local, wide-area, or peer-to-peer network, or may representa bus that is internal to a computing device (e.g., in exampleembodiments in which the computing device 2602 is contained in whole orin part within the device 2604). A storage medium 2608 may be anycomputer storage media. In one embodiment, the computing device 2602 mayinclude a virtual machine operating within another computing device. Inan alternative embodiment, the computing device 2602 may include avirtual machine operating within a program running on a remote server.

The computing device 2602 includes computer-executable instructions 2610that when executed on the computing device 2602 cause the computingdevice 2602 to (a) accept at least one indication of an interactioninvolving at least one member of a network; (b) create a personacorresponding to the at least one member of a network, wherein thepersona is at least partly based on the indication of an interaction;and (c) present the persona for use in the interaction involving the atleast one member of the network. As referenced above and as shown inFIG. 26, in some examples, the computing device 2602 may optionally becontained in whole or in part within the device 2604.

In FIG. 26, then, the system 2600 includes at least one computing device(e.g., 2602 and/or 2604). The computer-executable instructions 2610 maybe executed on one or more of the at least one computing device. Forexample, the computing device 2602 may implement the computer-executableinstructions 2610 and output a result to (and/or receive data from) thecomputing device 2604. Since the computing device 2602 may be wholly orpartially contained within the computing device 2604, the device 2604also may be said to execute some or all of the computer-executableinstructions 2610, in order to be caused to perform or implement, forexample, various ones of the techniques described herein, or othertechniques.

The device 2604 may include, for example, a portable computing device,workstation, or desktop computing device. In another example embodiment,the computing device 2602 is operable to communicate with the device2604 associated with the user 2612 to receive information about theinput from the user 2612 for performing data access and data processing,and present a persona for use in the interaction involving the at leastone member of the network, e.g., user 2612.

One skilled in the art will recognize that the herein describedcomponents (e.g., operations), devices, objects, and the discussionaccompanying them are used as examples for the sake of conceptualclarity and that various configuration modifications are contemplated.Consequently, as used herein, the specific exemplars set forth and theaccompanying discussion are intended to be representative of their moregeneral classes. In general, use of any specific exemplar is intended tobe representative of its class, and the non-inclusion of specificcomponents (e.g., operations), devices, and objects should not be takenlimiting.

Those skilled in the art will appreciate that the foregoing specificexemplary processes and/or devices and/or technologies arerepresentative of more general processes and/or devices and/ortechnologies taught elsewhere herein, such as in the claims filedherewith and/or elsewhere in the present application.

Those having skill in the art will recognize that the state of the arthas progressed to the point where there is little distinction leftbetween hardware and software implementations of aspects of systems; theuse of hardware or software is generally (but not always, in that incertain contexts the choice between hardware and software can becomesignificant) a design choice representing cost vs. efficiency tradeoffs.Those having skill in the art will appreciate that there are variousvehicles by which processes and/or systems and/or other technologiesdescribed herein can be effected (e.g., hardware, software, and/orfirmware), and that the preferred vehicle will vary with the context inwhich the processes and/or systems and/or other technologies aredeployed. For example, if an implementer determines that speed andaccuracy are paramount, the implementer may opt for a mainly hardwareand/or firmware vehicle; alternatively, if flexibility is paramount, theimplementer may opt for a mainly software implementation; or, yet againalternatively, the implementer may opt for some combination of hardware,software, and/or firmware. Hence, there are several possible vehicles bywhich the processes and/or devices and/or other technologies describedherein may be effected, none of which is inherently superior to theother in that any vehicle to be utilized is a choice dependent upon thecontext in which the vehicle will be deployed and the specific concerns(e.g., speed, flexibility, or predictability) of the implementer, any ofwhich may vary. Those skilled in the art will recognize that opticalaspects of implementations will typically employ optically-orientedhardware, software, and or firmware.

In some implementations described herein, logic and similarimplementations may include software or other control structures.Electronic circuitry, for example, may have one or more paths ofelectrical current constructed and arranged to implement variousfunctions as described herein. In some implementations, one or moremedia may be configured to bear a device-detectable implementation whensuch media hold or transmit one or more device detectable instructionsoperable to perform as described herein. In some variants, for example,implementations may include an update or modification of existingsoftware or firmware, or of gate arrays or programmable hardware, suchas by performing a reception of or a transmission of one or moreinstructions in relation to one or more operations described herein.Alternatively or additionally, in some variants, an implementation mayinclude special-purpose hardware, software, firmware components, and/orgeneral-purpose components executing or otherwise invokingspecial-purpose components. Specifications or other implementations maybe transmitted by one or more instances of tangible transmission mediaas described herein, optionally by packet transmission or otherwise bypassing through distributed media at various times.

Alternatively or additionally, implementations may include executing aspecial-purpose instruction sequence or invoking circuitry for enabling,triggering, coordinating, requesting, or otherwise causing one or moreoccurrences of virtually any functional operations described herein. Insome variants, operational or other logical descriptions herein may beexpressed as source code and compiled or otherwise invoked as anexecutable instruction sequence. In some contexts, for example,implementations may be provided, in whole or in part, by source code,such as C++, or other code sequences. In other implementations, sourceor other code implementation, using commercially available and/ortechniques in the art, may be compiled//implemented/translated/convertedinto a high-level descriptor language (e.g., initially implementingdescribed technologies in C or C++ programming language and thereafterconverting the programming language implementation into alogic-synthesizable language implementation, a hardware descriptionlanguage implementation, a hardware design simulation implementation,and/or other such similar mode(s) of expression). For example, some orall of a logical expression (e.g., computer programming languageimplementation) may be manifested as a Verilog-type hardware description(e.g., via Hardware Description Language (HDL) and/or Very High SpeedIntegrated Circuit Hardware Descriptor Language (VHDL)) or othercircuitry model which may then be used to create a physicalimplementation having hardware (e.g., an Application Specific IntegratedCircuit). Those skilled in the art will recognize how to obtain,configure, and optimize suitable transmission or computational elements,material supplies, actuators, or other structures in light of theseteachings.

The foregoing detailed description has set forth various embodiments ofthe devices and/or processes via the use of block diagrams, flowcharts,and/or examples. Insofar as such block diagrams, flowcharts, and/orexamples contain one or more functions and/or operations, it will beunderstood by those within the art that each function and/or operationwithin such block diagrams, flowcharts, or examples can be implemented,individually and/or collectively, by a wide range of hardware, software,firmware, or virtually any combination thereof. In one embodiment,several portions of the subject matter described herein may beimplemented via Application Specific Integrated Circuits (ASICs), FieldProgrammable Gate Arrays (FPGAs), digital signal processors (DSPs), orother integrated formats. However, those skilled in the art willrecognize that some aspects of the embodiments disclosed herein, inwhole or in part, can be equivalently implemented in integratedcircuits, as one or more computer programs running on one or morecomputers (e.g., as one or more programs running on one or more computersystems), as one or more programs running on one or more processors(e.g., as one or more programs running on one or more microprocessors),as firmware, or as virtually any combination thereof, and that designingthe circuitry and/or writing the code for the software and or firmwarewould be well within the skill of one of skill in the art in light ofthis disclosure. In addition, those skilled in the art will appreciatethat the mechanisms of the subject matter described herein are capableof being distributed as a program product in a variety of forms, andthat an illustrative embodiment of the subject matter described hereinapplies regardless of the particular type of signal bearing medium usedto actually carry out the distribution. Examples of a signal bearingmedium include, but are not limited to, the following: a recordable typemedium such as a floppy disk, a hard disk drive, a Compact Disc (CD), aDigital Video Disk (DVD), a digital tape, a computer memory, etc.; and atransmission type medium such as a digital and/or an analogcommunication medium (e.g., a fiber optic cable, a waveguide, a wiredcommunications link, a wireless communication link (e.g., transmitter,receiver, transmission logic, reception logic, etc.), etc.).

In a general sense, those skilled in the art will recognize that thevarious aspects described herein which can be implemented, individuallyand/or collectively, by a wide range of hardware, software, firmware,and/or any combination thereof can be viewed as being composed ofvarious types of “electrical circuitry.” Consequently, as used herein“electrical circuitry” includes, but is not limited to, electricalcircuitry having at least one discrete electrical circuit, electricalcircuitry having at least one integrated circuit, electrical circuitryhaving at least one application specific integrated circuit, electricalcircuitry forming a general purpose computing device configured by acomputer program (e.g., a general purpose computer configured by acomputer program which at least partially carries out processes and/ordevices described herein, or a microprocessor configured by a computerprogram which at least partially carries out processes and/or devicesdescribed herein), electrical circuitry forming a memory device (e.g.,forms of memory (e.g., random access, flash, read only, etc.)), and/orelectrical circuitry forming a communications device (e.g., a modem,communications switch, optical-electrical equipment, etc.). Those havingskill in the art will recognize that the subject matter described hereinmay be implemented in an analog or digital fashion or some combinationthereof.

Those skilled in the art will recognize that at least a portion of thedevices and/or processes described herein can be integrated into a dataprocessing system. Those having skill in the art will recognize that adata processing system generally includes one or more of a system unithousing, a video display device, memory such as volatile or non-volatilememory, processors such as microprocessors or digital signal processors,computational entities such as operating systems, drivers, graphicaluser interfaces, and applications programs, one or more interactiondevices (e.g., a touch pad, a touch screen, an antenna, etc.), and/orcontrol systems including feedback loops and control motors (e.g.,feedback for sensing position and/or velocity; control motors for movingand/or adjusting components and/or quantities). A data processing systemmay be implemented utilizing suitable commercially available components,such as those typically found in data computing/communication and/ornetwork computing/communication systems.

Those skilled in the art will recognize that it is common within the artto implement devices and/or processes and/or systems, and thereafter useengineering and/or other practices to integrate such implemented devicesand/or processes and/or systems into more comprehensive devices and/orprocesses and/or systems. That is, at least a portion of the devicesand/or processes and/or systems described herein can be integrated intoother devices and/or processes and/or systems via a reasonable amount ofexperimentation. Those having skill in the art will recognize thatexamples of such other devices and/or processes and/or systems mightinclude—as appropriate to context and application—all or part of devicesand/or processes and/or systems of (a) an air conveyance (e.g., anairplane, rocket, helicopter, etc.), (b) a ground conveyance (e.g., acar, truck, locomotive, tank, armored personnel carrier, etc.), (c) abuilding (e.g., a home, warehouse, office, etc.), (d) an appliance(e.g., a refrigerator, a washing machine, a dryer, etc.), (e) acommunications system (e.g., a networked system, a telephone system, aVoice over IP system, etc.), (f) a business entity (e.g., an InternetService Provider (ISP) entity such as Comcast Cable, Century Link,Southwestern Bell, etc.), or (g) a wired/wireless services entity (e.g.,Sprint, Verizon, AT&T, etc.), etc.

In certain cases, use of a system or method may occur in a territoryeven if components are located outside the territory. For example, in adistributed computing context, use of a distributed computing system mayoccur in a territory even though parts of the system may be locatedoutside of the territory (e.g., relay, server, processor, signal-bearingmedium, transmitting computer, receiving computer, etc. located outsidethe territory).

A sale of a system or method may likewise occur in a territory even ifcomponents of the system or method are located and/or used outside theterritory.

Further, implementation of at least part of a system for performing amethod in one territory does not preclude use of the system in anotherterritory.

All of the above U.S. patents, U.S. patent application publications,U.S. patent applications, foreign patents, foreign patent applicationsand non-patent publications referred to in this specification and/orlisted in any Application Data Sheet are incorporated herein byreference, to the extent not inconsistent herewith.

The herein described subject matter sometimes illustrates differentcomponents contained within, or connected with, different othercomponents. It is to be understood that such depicted architectures aremerely exemplary, and that in fact many other architectures may beimplemented which achieve the same functionality. In a conceptual sense,any arrangement of components to achieve the same functionality iseffectively “associated” such that the desired functionality isachieved. Hence, any two components herein combined to achieve aparticular functionality can be seen as “associated with” each othersuch that the desired functionality is achieved, irrespective ofarchitectures or intermedial components. Likewise, any two components soassociated can also be viewed as being “operably connected,” or“operably coupled,” to each other to achieve the desired functionality,and any two components capable of being so associated can also be viewedas being “operably couplable,” to each other to achieve the desiredfunctionality. Specific examples of operably couplable include but arenot limited to physically mateable and/or physically interactingcomponents, and/or wirelessly interactable, and/or wirelesslyinteracting components, and/or logically interacting, and/or logicallyinteractable components.

In some instances, one or more components may be referred to herein as“configured to,” “configured by,” “configurable to,” “operable/operativeto,” “adapted/adaptable,” “able to,” “conformable/conformed to,” etc.Those skilled in the art will recognize that such terms (e.g.“configured to”) can generally encompass active-state components and/orinactive-state components and/or standby-state components, unlesscontext requires otherwise.

With respect to the use of substantially any plural and/or singularterms herein, those having skill in the art can translate from theplural to the singular and/or from the singular to the plural as isappropriate to the context and/or application. The varioussingular/plural permutations are not expressly set forth herein for sakeof clarity.

While particular aspects of the present subject matter described hereinhave been shown and described, it will be apparent to those skilled inthe art that, based upon the teachings herein, changes and modificationsmay be made without departing from the subject matter described hereinand its broader aspects and, therefore, the appended claims are toencompass within their scope all such changes and modifications as arewithin the true spirit and scope of the subject matter described herein.It will be understood by those within the art that, in general, termsused herein, and especially in the appended claims (e.g., bodies of theappended claims) are generally intended as “open” terms (e.g., the term“including” should be interpreted as “including but not limited to,” theterm “having” should be interpreted as “having at least,” the term“includes” should be interpreted as “includes but is not limited to,”etc.). It will be further understood by those within the art that if aspecific number of an introduced claim recitation is intended, such anintent will be explicitly recited in the claim, and in the absence ofsuch recitation no such intent is present. For example, as an aid tounderstanding, the following appended claims may contain usage of theintroductory phrases “at least one” and “one or more” to introduce claimrecitations. However, the use of such phrases should not be construed toimply that the introduction of a claim recitation by the indefinitearticles “a” or “an” limits any particular claim containing suchintroduced claim recitation to claims containing only one suchrecitation, even when the same claim includes the introductory phrases“one or more” or “at least one” and indefinite articles such as “a” or“an” (e.g., “a” and/or “an” should typically be interpreted to mean “atleast one” or “one or more”); the same holds true for the use ofdefinite articles used to introduce claim recitations. In addition, evenif a specific number of an introduced claim recitation is explicitlyrecited, those skilled in the art will recognize that such recitationshould typically be interpreted to mean at least the recited number(e.g., the bare recitation of “two recitations,” without othermodifiers, typically means at least two recitations, or two or morerecitations). Furthermore, in those instances where a conventionanalogous to “at least one of A, B, and C, etc.” is used, in generalsuch a construction is intended in the sense one having skill in the artwould understand the convention (e.g., “a system having at least one ofA, B, and C” would include but not be limited to systems that have Aalone, B alone, C alone, A and B together, A and C together, B and Ctogether, and/or A, B, and C together, etc.). In those instances where aconvention analogous to “at least one of A, B, or C, etc.” is used, ingeneral such a construction is intended in the sense one having skill inthe art would understand the convention (e.g., “a system having at leastone of A, B, or C” would include but not be limited to systems that haveA alone, B alone, C alone, A and B together, A and C together, B and Ctogether, and/or A, B, and C together, etc.). It will be furtherunderstood by those within the art that typically a disjunctive wordand/or phrase presenting two or more alternative terms, whether in thedescription, claims, or drawings, should be understood to contemplatethe possibilities of including one of the terms, either of the terms, orboth terms unless context dictates otherwise. For example, the phrase “Aor B” will be typically understood to include the possibilities of “A”or “B” or “A and B.”

With respect to the appended claims, those skilled in the art willappreciate that recited operations therein may generally be performed inany order. Also, although various operational flows are presented in asequence(s), it should be understood that the various operations may beperformed in other orders than those which are illustrated, or may beperformed concurrently. Examples of such alternate orderings may includeoverlapping, interleaved, interrupted, reordered, incremental,preparatory, supplemental, simultaneous, reverse, or other variantorderings, unless context dictates otherwise. Furthermore, terms like“responsive to,” “related to,” or other past-tense adjectives aregenerally not intended to exclude such variants, unless context dictatesotherwise.

While various aspects and embodiments have been disclosed herein, otheraspects and embodiments will be apparent to those skilled in the art.The various aspects and embodiments disclosed herein are for purposes ofillustration and are not intended to be limiting, with the true scopeand spirit being indicated by the following claims.

What is claimed is:
 1. A personal information exposure reduction system,comprising: circuitry configured for accepting at least one indicationof an online financial transaction based at least partially on detectinga webpage presenting at least one of a checkout page, a shopping cartpage, an e-commerce page, or an online auction bid page including atleast one or more text entry fields of the detected page associated withrequests for personal information; circuitry configured for detecting atleast one value of the online financial transaction associated with thewebpage; circuitry configured for determining an amount of personalinformation of a persona for use with the webpage based at leastpartially on the at least one value in accordance with exposing minimalpersonal information in completing the online financial transaction;circuitry configured for creating the persona for use with the webpagebased at least partially on the amount of personal information;circuitry configured for attempting to complete the online financialtransaction including at least populating at least one text entry fieldof the webpage with corresponding personal information of the persona;and circuitry configured for determining whether the online financialtransaction was successful and, if the online financial transaction wasnot successful, adding personal information to the persona andattempting to complete the online financial transaction including atleast populating an additional text entry field of the webpage with theadded personal information of the persona.
 2. The personal informationexposure reduction system of claim 1, wherein circuitry configured foraccepting at least one indication of an online financial transactionbased at least partially on detecting a webpage presenting at least oneof a checkout page, a shopping cart page, an e-commerce page, or anonline auction bid page including at least one or more text entry fieldsof the detected page associated with requests for personal informationcomprises: circuitry configured to accept the at least one indicationbased at least partially on parsing at least one data stream received byat least one web application for at least some data indicative of the atleast one of a checkout page, a shopping cart page, an e-commerce page,or an online auction bid page and indicative of the one or more textentry fields.
 3. The personal information exposure reduction system ofclaim 1, wherein circuitry configured for determining an amount ofpersonal information of a persona for use with the webpage based atleast partially on the at least one value in accordance with exposingminimal personal information in completing the online financialtransaction comprises: circuitry configured for determining an amount ofpersonal information contained by the persona for use with the webpagebased at least partially on at least one dollar value category of atleast one item being purchased in the online financial transaction. 4.The personal information exposure reduction system of claim 1, whereincircuitry configured for accepting at least one indication of an onlinefinancial transaction based at least partially on detecting a webpagepresenting at least one of a checkout page, a shopping cart page, ane-commerce page, or an online auction bid page including at least one ormore text entry fields of the detected page associated with requests forpersonal information comprises: circuitry configured to accept at leastone indication of an online financial transaction conducted via at leasta web browser.
 5. The personal information exposure reduction system ofclaim 1, wherein circuitry configured for accepting at least oneindication of an online financial transaction based at least partiallyon detecting a webpage presenting at least one of a checkout page, ashopping cart page, an e-commerce page, or an online auction bid pageincluding at least one or more text entry fields of the detected pageassociated with requests for personal information comprises: circuitryconfigured to detect the at least one indication via at least one of anX/Y coordinate web page reader, a web page image reader, or a screenscraper.
 6. The personal information exposure reduction system of claim1, wherein circuitry configured for creating the persona for use withthe webpage based at least partially on the amount of personalinformation comprises: circuitry configured to obtain one or moreelements of personal information corresponding to a user initiating theonline financial transaction for use in the persona, including at leastobtaining at least one element of personal information via accessing,via the internet, at least one bank account associated with the user toobtain the at least one element of personal information from the atleast one bank account.
 7. The personal information exposure reductionsystem of claim 1, wherein circuitry configured for determining anamount of personal information of a persona for use with the webpagebased at least partially on the at least one value in accordance withexposing minimal personal information in completing the online financialtransaction comprises: circuitry configured for determining an amount ofpersonal information of a persona for use with the webpage based atleast partially on the at least one value, including at leastcorrelating the at least one value with a persona-creation rulesetrelating one or more values with a hierarchy of personal information inaccordance with exposing minimal personal information in completing theonline financial transaction.
 8. The personal information exposurereduction system of claim 1, wherein circuitry configured for attemptingto complete the online financial transaction including at leastpopulating at least one text entry field of the webpage withcorresponding personal information of the persona comprises: circuitryconfigured to present the persona via a mobile device associated with auser at a vendor's physical establishment for use in a purchase from thevendor.
 9. The personal information exposure reduction system of claim8, wherein circuitry configured to present the persona via a mobiledevice associated with a user at a vendor's physical establishment foruse in a purchase from the vendor comprises: circuitry configured totransmit at least a portion of the persona at least partially via themobile device, the mobile device capable of wirelessly interacting withthe at least one of a checkout page, a shopping cart page, an e-commercepage, or an online auction bid page provided at least partially by adevice reader at the vendor's physical establishment.
 10. The personalinformation exposure reduction system of claim 1, wherein circuitryconfigured for accepting at least one indication of an online financialtransaction based at least partially on detecting a webpage presentingat least one of a checkout page, a shopping cart page, an e-commercepage, or an online auction bid page including at least one or more textentry fields of the detected page associated with requests for personalinformation comprises: circuitry configured to accept at least oneindication of an online financial transaction conducted by at least oneof a robotic user or a real-world user.
 11. The personal informationexposure reduction system of claim 1, wherein the circuitry configuredfor accepting, the circuitry configured for detecting, the circuitryconfigured for determining an amount of personal information, thecircuitry configured for creating, the circuitry configured forattempting, and the circuitry configured for determining whether theonline financial transaction was successful are effected within a mobiledevice.
 12. The personal information exposure reduction system of claim1, wherein circuitry configured for creating the persona for use withthe webpage based at least partially on the amount of personalinformation comprises: circuitry configured for creating the persona foruse with the webpage based at least partially on the amount of personalinformation and based at least partially on a vendor-specific personadatabase, including at least populating the persona based at leastpartially on at least some information from the vendor-specific personadatabase relating to what personal information is required by the vendorassociated with the webpage.
 13. The personal information exposurereduction system of claim 1, wherein circuitry configured fordetermining whether the online financial transaction was successful and,if the online financial transaction was not successful, adding personalinformation to the persona and attempting to complete the onlinefinancial transaction including at least populating an additional textentry field of the webpage with the added personal information of thepersona comprises: circuitry configured for detecting at least oneindication of an approval of the online financial transaction by aninteraction partner associated with the at least one of a checkout page,a shopping cart page, an e-commerce page, or an online auction bid page,including at least circuitry configured to parse the data streamassociated with the online financial transaction for one or more wordsindicative of a successful transaction.
 14. The personal informationexposure reduction system of claim 1, wherein circuitry configured fordetermining whether the online financial transaction was successful and,if the online financial transaction was not successful, adding personalinformation to the persona and attempting to complete the onlinefinancial transaction including at least populating an additional textentry field of the webpage with the added personal information of thepersona comprises: circuitry configured for determining whether theonline financial transaction was successful and, if the online financialtransaction was not successful, revising the persona including at leastpopulating an additional text entry field, the additional text entryfield associated with at least one of red type or an asterisk, andattempting to complete the online financial transaction with the revisedpersona.
 15. The personal information exposure reduction system of claim1, wherein circuitry configured for detecting at least one value of theonline financial transaction associated with the webpage comprises:circuitry configured for detecting at least one value of the onlinefinancial transaction associated with the webpage at least partially viaparsing a data stream associated with the online financial transactionfor one or more numbers in proximity of at least one word indicative ofthe at least one value of the online financial transaction.
 16. Thepersonal information exposure reduction system of claim 1, whereincircuitry configured for detecting at least one value of the onlinefinancial transaction associated with the webpage comprises: circuitryconfigured for accepting at least some markup language code from thewebpage indicative of at least one dollar value of at least one purchaseor at least one auction bid.
 17. The personal information exposurereduction system of claim 1, wherein circuitry configured fordetermining an amount of personal information of a persona for use withthe webpage based at least partially on the at least one value inaccordance with exposing minimal personal information in completing theonline financial transaction comprises: circuitry configured fordetermining that an alias of a user associated with initiating theonline financial transaction should be populated within the persona atleast partially based on the at least one value.
 18. The personalinformation exposure reduction system of claim 1, wherein circuitryconfigured for creating the persona for use with the webpage based atleast partially on the amount of personal information comprises:circuitry configured to obtain one or more elements of personalinformation corresponding to a user initiating the online financialtransaction for use in the persona, including at least obtaining atleast one element of personal information via accessing, via theinternet, at least one social network account associated with the userto obtain the at least one element of personal information from the atleast one social network account.
 19. A personal information exposurereduction computer program product, comprising: at least onenon-transitory computer-readable medium including at least: one or moreinstructions for accepting at least one indication of an onlinefinancial transaction based at least partially on detecting a webpagepresenting at least one of a checkout page, a shopping cart page, ane-commerce page, or an online auction bid page, including at least oneor more text entry fields of the detected page associated with requestsfor personal information; one or more instructions for detecting atleast one value of the online financial transaction associated with thewebpage; one or more instructions for determining an amount of personalinformation of a persona for use with the webpage based at leastpartially on the at least one value in accordance with exposing minimalpersonal information in completing the online financial transaction; oneor more instructions for creating the persona for use with the webpagebased at least partially on the amount of personal information; one ormore instructions for attempting to complete the online financialtransaction including at least populating at least one text entry fieldof the webpage with corresponding personal information of the persona;and one or more instructions for determining whether the onlinefinancial transaction was successful and, if the online financialtransaction was not successful, adding personal information to thepersona and attempting to complete the online financial transcationincluding at least populating an additional text entry field of thewebpage with the added personal information of the persona.
 20. Apersonal information exposure reduction method, comprising: accepting atleast one indication of an online financial transaction based at leastpartially on detecting a webpage presenting at least one of a checkoutpage, a shopping cart page, an e-commerce page, or an online auction bidpage including at least one or more text entry fields of the detectedpage associated with requests for personal information; detecting atleast one value of the online financial transaction associated with thewebpage; determining an amount of personal information of a persona foruse with the webpage based at least partially on the at least one valuein accordance with exposing minimal personal information in completingthe online financial transaction; creating the persona for use with thewebpage based at least partially on the amount of personal information;attempting to complete the online financial transaction including atleast populating at least one text entry field of the webpage withcorresponding personal information of the persona; and determiningwhether the online financial transaction was successful and, if theonline financial transaction was not successful, adding personalinformation to the persona and attempting to complete the onlinefinancial transaction including at least populating an additional textentry field of the webpage with the added personal information of thepersona.